Peer-to-peer neighborhood delivery multi-copter and method

ABSTRACT

A method, device and system of an autonomous neighborhood multi-copter commerce network in a community are disclosed. In one embodiment, an autonomous neighborhood multi-copter includes a storage compartment of the autonomous neighborhood multi-copter in which items are storable, a computer system of the autonomous neighborhood multi-copter that is communicatively coupled to a commerce server of a neighborhood communication system through a wireless network to autonomously navigate the autonomous neighborhood multi-copter to a destination in the neighborhood specified by the commerce server using a peer-to-peer network of client side devices in the neighborhood that are geo-constrained to a location of a defined neighborhood, and a navigation server of the autonomous neighborhood multi-copter to provide a remote sensing capability to the autonomous neighborhood multi-copter such that the autonomous neighborhood multi-copter is autonomously navigable to the destination using the peer-to-peer network.

CLAIMS OF PRIORITY

This patent application is a continuation and continuation in part,claims priority from, and hereby incorporates by reference and claimspriority from the entirety of the disclosures of the following cases andeach of the cases on which they depend and further claim priority orincorporate by reference:

-   (1) U.S. Utility patent application Ser. No. 11/653,194 titled    ‘LODGING AND REAL PROPERTY IN A GEO-SPATIAL MAPPING ENVIRONMENT’    filed on Jan. 12, 2007.-   (2) U.S. Utility patent application Ser. No. 11/731,465 titled    ‘WHITE PAGES AND YELLOW PAGE DIRECTORIES IN A GEO-SPATIAL    ENVIRONMENT, filed on Mar. 29, 2007.-   (3) U.S. Utility patent application Ser. No. 11/827,400 titled ‘HOT    NEWS NEIGHBORHOOD BANTER IN A GEO-SPATIAL SOCIAL NETWORK’ filed on    Jul. 10, 2007.-   (4) U.S. Utility patent application Ser. No. 14/142,764 titled    ‘DRIVERLESS VEHICLE COMMERCE NETWORK AND COMMUNITY’ filed on Dec.    28, 2013.-   (5) U.S. Utility patent application Ser. No. 14/157,540 titled    ‘AUTONOMOUS NEIGHBORHOOD VEHICLE COMMERCE NETWORK AND COMMUNITY’    filed on Jan. 17, 2014.

FIELD OF TECHNOLOGY

This disclosure relates generally to the technical fields ofcommunications and, in one example embodiment, to a method, apparatus,and system of a peer-to-peer neighborhood delivery multi-copter andmethod.

BACKGROUND

Individuals may wish to acquire a variety of items. However, theseindividuals may not have the time and/or means to pick up these goods.Individuals may not have access to a vehicle and/or may live in an areawhere public transportation and/or other means of travel are unreliable,expensive and/or unsafe. Those with access to means of transportationmay not wish to waste hours traveling to and from locations and/orattaining items. Individuals may not have time to complete these errandsas work and/or other engagements may get in the way. Additionally,individuals may not wish to order online as they lack the time to waitfor shipping. As a result, precious time may be wasted and/or errandsforegone as a result of a lack of ability to complete them.

Home delivery services may be expensive, require tips and/or haveinconvenient hours of operation and/or uncertain arrival times.Furthermore, individuals may not trust currier services to handle itemsand/or may feel that their items are not secure in transit. Individualsmay have no way to conveniently acquire and/or deliver items withoutinvesting significant amounts of time, money and/or effort. As a result,time and money may be wasted and/or valuable opportunities for commercemay be lost.

SUMMARY

Disclosed are a method, a device and/or a system for autonomousneighborhood multi-copter commerce through a commerce server of aneighborhood communication network, according to one embodiment.

In one aspect, an autonomous neighborhood multi-copter includes astorage compartment of the autonomous neighborhood multi-copter in whichitems are storable, a computer system of the autonomous neighborhoodmulti-copter that is communicatively coupled to a commerce server of aneighborhood communication system through a wireless network toautonomously navigate the autonomous neighborhood multi-copter to adestination in the neighborhood specified by the commerce server using apeer-to-peer network of client side devices in the neighborhood that aregeo-constrained to a location of a defined neighborhood, and anavigation server of the autonomous neighborhood multi-copter to providea remote sensing capability to the autonomous neighborhood multi-coptersuch that the autonomous neighborhood multi-copter is autonomouslynavigable to the destination using the peer-to-peer network.

In an alternate aspect, an autonomous neighborhood multi-copter includesa set of wheels and a set of propellers aligned in a pattern to providethe autonomous neighborhood multi-copter stability when traversing aflight path, a sidewalk, a bike lane, and a roadway. In this embodiment,the autonomous neighborhood multi-copter can both fly and traverse land(e.g., when battery is low and when conditions warrant). The autonomousneighborhood multi-copter also comprises of a storage compartment of theautonomous neighborhood multi-copter in which items are storable, anelectronic locking mechanism of the storage compartment, a computersystem of the autonomous neighborhood multi-copter that iscommunicatively coupled to a commerce server of a neighborhoodcommunication system through a wireless network to autonomously navigatethe autonomous neighborhood multi-copter to a destination specified bythe commerce server, and a navigation server of the autonomousneighborhood multi-copter to provide a remote sensing capability to theautonomous neighborhood multi-copter such that the autonomousneighborhood multi-copter is autonomously navigable to the destination.

A sensor fusion algorithm may be utilized through which at least some ofan ultrasound unit, a radar unit, a light sensor, a LIDAR unit, apropeller/wheel encoding sensor, an accelerometer sensor, a gyroscopicsensor, a compass sensor, and/or a stereo optical sensor operate inconcert to provide a three dimensional environmental view of anenvironment surrounding the autonomous neighborhood multi-copter to theautonomous neighborhood multi-copter. A sidewalk detection sensor mayprovide a sidewalk detection sensor through which the autonomousneighborhood multi-copter may detect a gradation rise caused by asidewalk start location and/or a gradation drop caused by a sidewalk endlocation. A telescoping platform coupled to a base of the autonomousneighborhood multi-copter may automatically displace a set of frontwheels to rise and/or fall based on the detected one of the gradationrise caused by the sidewalk start location and/or the gradation dropcaused by the sidewalk end location to provide mechanical stability forthe item in the storage compartment of the autonomous neighborhoodmulti-copter.

A heartbeat message may be periodically transmitted to the commerceserver having a set of current geo-spatial coordinates of the autonomousneighborhood multi-copter, a time stamp, a date stamp, and/or anoperational status of the vehicle. An emergency broadcast message may beautomatically generated to a set of neighbors in a geo-spatial vicinityof the autonomous neighborhood multi-copter when the autonomousneighborhood multi-copter detects a failure condition comprising animpact, a mechanical failure, an electrical failure, and/or a damagecondition. The emergency broadcast message may include a photo data, ageo-spatial coordinates data, a video data, an audio data, a timeoutcondition of the heartbeat message receipt at the commerce server,and/or a textual data associated with the failure condition. Theautonomous neighborhood multi-copter may automatically park itself in agarage structure associated with an operator of the autonomousneighborhood multi-copter adjacent to a passenger vehicle, wherein theoperator is at least one an individual, a family, a business, an owner,and/or a lessee, according to one embodiment.

The storage compartment may be temperature regulated to maintain atemperature of an item in transit between a starting address associatedwith a merchant and/or a neighbor in a neighborhood in a geospatialvicinity of the autonomous neighborhood multi-copter, and/or adestination address associated with a recipient of the item in theneighborhood in the geospatial vicinity of the autonomous neighborhoodmulti-copter, wherein the neighborhood boundary is defined through aneighborhood boundary data provider. The autonomous neighborhoodmulti-copter may be in a form of an autonomous neighborhood aerialvehicle having a detachable storage compartment thereon, and/or havingan ability to autonomously traverse through flight paths based oncommands from the commerce server.

In another aspect, a method of an autonomous neighborhood multi-coptercomprising associating the autonomous neighborhood multi-copter with anon-transient location and determining, through a commerce server of aneighborhood communication system, that a destination in a thresholdradial distance from the non-transient location is received by theautonomous neighborhood multi-copter through a wireless network. Themethod also includes determining an optimal route from the currentlocation of the autonomous neighborhood multi-copter to the destinationand traveling autonomously on the optimal route to the destination.

A current location of the autonomous neighborhood multi-copter may beperiodically determined through a processor. The current location of theautonomous neighborhood multi-copter may be communicated to the commerceserver. A set of light emitting diodes encompassing the autonomousneighborhood multi-copter may be automatically activated when a lightsensor detects that an environmental brightness is below a thresholdluminosity. An envelope may be generated around the autonomousneighborhood multi-copter, wherein the envelope includes a set ofminimum ranges. The set of minimum ranges may include a minimum distancethat must be kept in a direction in front, behind, to a left, to aright, above, and/or below the autonomous neighborhood multi-copter.

A range of speed the autonomous vehicle may reach and a minimum and/or amaximum distance traveled by the autonomous neighborhood multi-coptermay be established. The minimum and/or the maximum distance traveled bythe autonomous neighborhood multi-copter may be set for a per trip, perday and/or a per delivery distance traveled. A maximum magnitude ofdeceleration may be established. The maximum magnitude of decelerationmay be measured in feet per second squared. A minimum crosswalkproximity at which the autonomous neighborhood multi-copter is permittedto stop may be established.

It may be determined at a predetermined interval if a different routethat is more efficient than the optimal route exists based on a deliverytime, a pendency of time, and/or a minimal travel distance. Thepredetermined interval for determining if a different route is moreefficient than the optimal route exists may include constantlydetermining, determining every minute, determining every one hundredyards, when the autonomous neighborhood multi-copter encounters traffic,when the autonomous neighborhood multi-copter encounters the object. Adifferent route may be calculated. The different route may be traveledalong as long as the different route remains a most efficient route. Itmay be determined when an alternate field of view is needed. Establishedconstraints of the envelope, the speed, the distance traveled, themaximum magnitude of deceleration and/or the minimum crosswalk proximitymay be prioritized in respect to the need to establish the alternatefield of view. An optimal alternate field of view that does not violateestablished constraints prioritized above obtaining the alternate fieldof view may be determined. The optimal alternate field of view may beobtained without violating constraints prioritized above obtaining thealternate field of view.

Obtaining the optimal alternate field of view without violatingconstraints prioritized above obtaining the alternate field of view mayinvolve switching sensors, moving the autonomous neighborhoodmulti-copter and/or moving sensors. The set of minimum ranges of theenvelope may depend on a speed of the autonomous neighborhoodmulti-copter, a set of weather conditions, an environment of theautonomous neighborhood multi-copter, the item, and/or a nature of theobject that is in close proximity with the autonomous neighborhoodmulti-copter. The storage compartment may be temperature regulated tomaintain a temperature and/or a humidity of an item in transit between astarting address associated with a merchant and/or a neighbor in aneighborhood in a geospatial vicinity of the autonomous neighborhoodmulti-copter, and/or a destination location associated with a recipientof the item in the neighborhood in the geospatial vicinity of theautonomous neighborhood multi-copter. The neighborhood boundary may bedefined through a neighborhood boundary data provider, and/or thestorage compartment may be equipped with a suspension device to protectthe item in the storage compartment while in transit.

An emergency broadcast message may be automatically generated to a setof neighbors in a geo-spatial vicinity of the autonomous neighborhoodmulti-copter when the autonomous neighborhood multi-copter detects afailure condition comprising an impact, a mechanical failure, anelectrical failure, and/or a damage condition. The emergency broadcastmessage may include a photo data, a geo-spatial coordinates data, avideo data, an audio data, a timeout condition of a heartbeat messagereceipt at the commerce server, and/or a textual data associated withthe failure condition. A heartbeat message may be periodicallytransmitted to the commerce server having a set of current geo-spatialcoordinates of the autonomous neighborhood multi-copter, a time stamp, adate stamp, and/or an operational status of the vehicle. Emergencyresponse services may be automatically contacted when the autonomousneighborhood multi-copter detects a crime, an accident involving thirdparties and/or an attempted tampering with the autonomous neighborhoodmulti-copter.

The contacting may include a time stamp, the geo-spatial coordinatesdata, the photo data, the video data, the audio data, and/or the textualdata. Emergency response services may include a police station, a firestation and/or a medical responder. A set of predicted behaviors ofdetected objects within a threshold distance from the autonomousneighborhood multi-copter may be calculated. Confidence levels for thepredicted behaviors may be determined. The confidence levels may be anumber and/or a percentage of the probability of each predicted behavioroccurring. Confidence levels for the predicted behaviors may be adjustedbased on a change in location, a change in speed, a change of direction,a change in angle and/or observed behavior. An item may be vended fromthe storage compartment and ejecting the item from an ejection module.The item may be ejected through an air based propulsion system alignedthrough a camera adjacent to the ejection module.

A stop sign may be detected and/or the autonomous neighborhoodmulti-copter may automatically stop at the appropriate point when thestop sign is detected. A yield sign may be detected and/or theautonomous neighborhood multi-copter may automatically monitor and/oryield to a traffic flow at an intersection in the neighborhood. It maybe detected when a pedestrian is walking and/or an entity is air born ina path proximate to the autonomous neighborhood multi-copter. It may bedetected when a bicyclist is biking in a path proximate to theautonomous neighborhood multi-copter. A credit payment may be acceptedusing a magnetic card reader of the autonomous neighborhoodmulti-copter, a near-field credit scanner of the autonomous neighborhoodmulti-copter, and/or a biometric payment reader of the autonomousneighborhood multi-copter. The commerce server may be in a privacyserver of the neighborhood communication system that may be wirelesslycoupled with the autonomous neighborhood multi-copter.

The privacy server may be a community network comprising verifying thateach user of the community network lives at a residence associated witha claimable residential address of the community network formed througha social community module of a privacy server using a processor and/or amemory. The privacy server may be a community network comprisingobtaining from each user of the community network, using the processorof a data processing system, member data associated with each user, themember data including an address, and associating the address with aprofile of each user. The privacy server may be a community networkcomprising determining a location of each user based on the member data,storing the member data in a database, and obtaining a personal addressprivacy preference from each user, the personal address privacypreference specifying if the address should be displayed to other users.

A geospatial representation of a set of points on a map definingresidences associated with each user of the community network having themember data may be generated using a mapping server associated with theprivacy server through a network. A particular user of a third-partyapplication may be authenticated, using a verify module of the privacyserver, as being a verified user of the neighborhood communicationsystem having a verified residential address in the neighborhoodcommunication system. A social graph of the particular user may becommunicated, using the verify module of the privacy server, based onthe personal address privacy preference of the particular user to thethird-party application. The verified residential address may beprovided, using the verify module of the privacy server, to thethird-party application based on the authentication of the particularuser of the third-party application as being the verified user of theneighborhood communication system.

An address verification algorithm associated with each user of theonline community may be applied to verify that each user lives at aresidence associated with a claimable residential address of an onlinecommunity formed through a social community module of the privacy serverusing the processor and/or the memory. The mapping server may generate alatitudinal data and/or a longitudinal data associated with eachclaimable residential address of the online community associated witheach user of the online community. The privacy server may automaticallydetermine a set of access privileges in the online community associatedwith each user of the online community by constraining access in theonline community based on a neighborhood boundary determined using aBezier curve algorithm of the privacy server. The privacy server maytransform the claimable residential address into a claimed address uponan occurrence of an event.

The privacy server may instantiate the event when a particular user isassociated with the claimable residential address based on averification of the particular user as living at a particularresidential address associated with the claimable residential addressusing the privacy server. The privacy server may constrain theparticular user to communicate through the online community only with aset of neighbors having verified addresses using the privacy server. Theprivacy server may define the set of neighbors as other users of theonline community that have each verified their addresses in the onlinecommunity using the privacy server and/or which have each claimedresidential addresses that are in a threshold radial distance from theclaimed address of the particular user.

In yet another aspect, a neighborhood communication system comprising acommerce server, a wireless network, and a set of autonomousneighborhood multi-copters that are communicatively coupled to thecommerce server of the neighborhood communication system through thewireless network to autonomously travel to destinations specified by thecommerce server. Each of the set of autonomous neighborhoodmulti-copters periodically transmits heartbeat messages to the commerceserver having a set of current geo-spatial coordinates of each of theautonomous neighborhood multi-copters, a time stamp, a date stamp, andan operational status of each of the autonomous neighborhoodmulti-copters. At least some of the autonomous neighborhoodmulti-copters are in a form of autonomous neighborhood aerial vehicleseach having a detachable storage compartment thereon, and having anability to autonomously traverse through bicycle lanes adjacent to aroadway based on commands from the commerce server.

A sensory fusion algorithm may be utilized through which at least someof an ultrasound unit, a radar unit, a light sensor, a LIDAR unit, awheel encoding sensor, an accelerometer sensor, a gyroscopic sensor, acompass sensor, and/or a stereo optical sensor operate in concert toprovide a three dimensional environmental view to the autonomousneighborhood multi-copter of an environment surrounding each of theautonomous neighborhood multi-copter. A particular autonomousneighborhood multi-copter may automatically generate an emergencybroadcast message to a set of neighbors in a geo-spatial vicinity of theparticular autonomous neighborhood multi-copter when the particularautonomous neighborhood multi-copter detects a failure conditioncomprising an impact, a mechanical failure, an electrical failure,and/or a damage condition, wherein the emergency broadcast messageincludes a photo data, a geo-spatial coordinates data, a video data, anaudio data, a timeout condition of the heartbeat message receipt at thecommerce server, and/or a textual data associated with the failurecondition.

Each of the autonomous neighborhood multi-copters automatically may beable to park themselves in a garage structure associated with anoperator of the autonomous neighborhood multi-copter adjacent to apassenger vehicle. The operator may be at least one an individual, afamily, a business, an owner, and/or a lessee. The storage compartmentmay be temperature regulated to maintain a temperature of an item intransit between a starting address associated with a merchant and/or aneighbor in a neighborhood in a geospatial vicinity of the autonomousneighborhood multi-copter, and/or a destination address associated witha recipient of the item in the neighborhood in the geospatial vicinityof the autonomous neighborhood multi-copter. The neighborhood boundarymay be defined through a neighborhood boundary data provider.

The methods, systems, and apparatuses disclosed herein may beimplemented in any means for achieving various aspects, and may beexecuted in a form of a machine-readable medium embodying a set ofinstructions that, when executed by a machine, cause the machine toperform any of the operations disclosed herein. Other features will beapparent from the accompanying drawings and from the detaileddescription that follows.

BRIEF DESCRIPTION OF THE DRAWINGS

Example embodiments are illustrated by way of example and not limitationin the figures of the accompanying drawings, in which like referencesindicate similar elements and in which:

FIG. 1A is a view of an autonomous neighborhood multi-copter, accordingto one embodiment.

FIG. 1B is a neighborhood view of the autonomous neighborhoodmulti-copter of FIG. 1A operating in a neighborhood environment,according to one environment.

FIG. 2 is a functional block diagram illustrating the autonomousneighborhood multi-copter of FIG. 1A, according to one embodiment.

FIG. 3A is a scenario of the autonomous neighborhood on the side of theroad predicting bicycle behavior, according to one embodiment.

FIG. 3B is a scenario of the autonomous neighborhood multi-copterpredicting car behavior, according to one embodiment.

FIG. 3C is a scenario of the autonomous neighborhood multi-copter in abike lane predicating bicycle behavior, according to one embodiment.

FIG. 4 is a scan view of the autonomous neighborhood multi-copter ofFIG. 1A detecting an object, according to one embodiment.

FIG. 5A is a multi scan view of the autonomous neighborhood multi-copterof FIG. 1A performing a multi sensor scan of its environment, accordingto one embodiment.

FIG. 5B is a multi scan view of the autonomous neighborhood multi-copterof FIG. 5A using multiple sensor systems to scan overlapping fields ofview, according to one embodiment.

FIG. 6 is an internal sensor system view of the sensor system, accordingto one embodiment.

FIG. 7 illustrates the sensor system as a LIDAR sensor, according to oneembodiment.

FIG. 8 is a path adjustment view 850 of the autonomous neighborhoodmulti-copter of FIG. 1A rerouting around an object, according to oneembodiment.

FIG. 9A is an envelope view of an envelope of the autonomousneighborhood multi-copter of FIG. 1A, according to one embodiment.

FIG. 9B is an envelope implementation view of the autonomousneighborhood multi-copter of FIG. 9A maintaining its envelope inpedestrian traffic, according to one embodiment.

FIG. 9C is a caravan view of the autonomous neighborhood multi-copter ofFIG. 9B in a caravan with multiple other autonomous neighborhoodmulti-copters, according to one embodiment.

FIG. 10 is a break time view of a minimum break time calculation,according to one embodiment.

FIG. 11 is a GPS monitoring view of a possible autonomous neighborhoodmulti-copter location, according to one embodiment.

FIG. 12 is a location identification view determining the location ofthe autonomous neighborhood multi-copter from possible locations,according to one embodiment.

FIG. 13A is an exemplary range scan of a first range scan, according toone embodiment.

FIG. 13B is an exemplary range scan of a second range scan, according toone embodiment.

FIG. 14 is a user interface view of a group view associated withparticular geographical location, according to one embodiment.

FIG. 15 is a user interface view of claim view, according to oneembodiment.

FIG. 16 is a user interface view of a building builder, according to oneembodiment.

FIG. 17 is a systematic view of communication of claimable data,according to one embodiment.

FIG. 18 is a systematic view of a network view, according to oneembodiment.

FIG. 19 is a block diagram of a database, according to one embodiment.

FIG. 20 is an exemplary graphical user interface view for datacollection, according to one embodiment.

FIG. 21 is an exemplary graphical user interface view of imagecollection, according to one embodiment.

FIG. 22 is an exemplary graphical user interface view of an invitation,according to one embodiment.

FIG. 23 is a flowchart of inviting the invitee(s) by the registereduser, notifying the registered user upon the acceptance of theinvitation by the invitee(s) and, processing and storing the input dataassociated with the user in the database, according to one embodiment.

FIG. 24 is a flowchart of adding the neighbor to the queue, according toone embodiment.

FIG. 25 is a flowchart of communicating brief profiles of the registeredusers, processing a hyperlink selection from the verified registereduser and calculating and ensuring the Nmax degree of separation of theregistered users away from verified registered users, according to oneembodiment.

FIG. 26 is an N degree separation view, according to one embodiment.

FIG. 27 is a user interface view showing a map, according to oneembodiment.

FIG. 28A is a process flow chart of searching a map based community andneighborhood contribution, according to one embodiment.

FIG. 28B is a continuation of process flow of FIG. 28A showingadditional processes, according to one embodiment.

FIG. 28C is a continuation of process flow of FIG. 28B showingadditional processes, according to one embodiment.

FIG. 28D is a continuation of process flow of FIG. 28C showingadditional processes, according to one embodiment.

FIG. 28E is a continuation of process flow of FIG. 28D showingadditional processes, according to one embodiment.

FIG. 29 is a system view of a global neighborhood environmentcommunicating with the neighborhood(s) through a network, anadvertiser(s), a global map data and an occupant data according to oneembodiment.

FIG. 30 is an exploded view of a social community module of FIG. 29,according to one embodiment.

FIG. 31 is an exploded view of a search module of FIG. 29, according toone embodiment.

FIG. 32 is an exploded view of a claimable module of FIG. 29, accordingto one embodiment.

FIG. 33 is an exploded view of a commerce module of FIG. 29, accordingto one embodiment.

FIG. 34 is an exploded view of a map module of FIG. 29, according to oneembodiment.

FIG. 35 is a table view of user address details, according to oneembodiment.

FIG. 36 is a social community view of a social community module,according to one embodiment.

FIG. 37 is a profile view of a profile module, according to oneembodiment.

FIG. 38 is a contribute view of a neighborhood network module, accordingto one embodiment.

FIG. 39 is a diagrammatic system view of a data processing system inwhich any of the embodiments disclosed herein may be performed,according to one embodiment.

FIG. 40A is a user interface view of mapping user profile of thegeographical location, according to one embodiment.

FIG. 40B is a user interface view of mapping of the claimable profile,according to one embodiment.

FIG. 41A is a user interface view of mapping of a claimable profile ofthe commercial user, according to one embodiment.

FIG. 41B is a user interface view of mapping of customizable businessprofile of the commercial user, according to one embodiment.

FIG. 42 is a neighborhood communication network view of a commerceserver having a radial distribution module communicating with a dataprocessing system that generates a radial broadcast through an internetprotocol network using a radial algorithm of the radial distributionmodule of the commerce server, according to one embodiment.

FIG. 43A shows an autonomous neighborhood bicycle, according to oneembodiment.

FIG. 43B shows the autonomous neighborhood bicycle of FIG. 43A afterbeing collapsed, according to one embodiment.

FIG. 44 is a cross sectional view of a storage compartment showingseparate compartments and an ejection module, according to oneembodiment.

FIG. 45 is a cross sectional view of a storage compartment showing anitem and warming trays, according to one embodiment.

FIG. 46A is a sidewalk traversing view of the autonomous neighborhoodmulti-copter mounting a sidewalk, according to one embodiment.

FIG. 46B is a sidewalk traversing view of the autonomous neighborhoodmulti-copter dismounting a sidewalk, according to one embodiment.

FIG. 47 is a collision identification view of trajectory paths,according to one embodiment.

FIG. 48 is a collision identification view of identification of midwayposition index locations of each boundary box, according to oneembodiment.

FIG. 49 is a collision identification view of subdivided boundary boxregeneration, according to one embodiment.

FIG. 50 is a collision identification view showing the identification ofthe midway position index locations of each regeneration boundary box,according to one embodiment.

FIG. 51 is a collision identification view of a final set of regeneratedboundary boxes, according to one embodiment.

FIG. 52 is an intersection view of the autonomous neighborhoodmulti-copter of FIG. 1A at an intersection, according to one embodiment.

FIG. 53 is a user interface view of the data processing system of FIG.42 displaying an autonomous neighborhood multi-copter map, according toone embodiment.

FIG. 54 is an autonomous neighborhood multi-copter alert user interfaceview of the data processing system of FIG. 42 receiving an autonomousneighborhood multi-copter alert, according to one embodiment.

FIG. 55 is a three dimensional environmental view of the autonomousneighborhood multi-copter of FIG. 1A using a LIDAR sensor to scan itsenvironment, according to one embodiment.

FIG. 56 is a garage view of a family garage with the autonomousneighborhood multi-copter of FIG. 1A and two autonomous cars, accordingto one embodiment.

FIG. 57 is an emergency broadcast view of the data processing system ofFIG. 42 receiving an emergency broadcast message, according to oneembodiment.

FIG. 58A is a weather traversing view of the autonomous neighborhoodmulti-copter traveling in windy conditions, according to one embodiment.

FIG. 58B is a weather traversing view of the autonomous neighborhoodmulti-copter of FIG. 58A traveling in windy conditions, according to oneembodiment.

FIG. 59 is an aerial traffic navigation view of the autonomousneighborhood multi-copter interacting with other autonomous neighborhoodmulti-copters in the same air space, according to one embodiment.

FIG. 60 is a notification graphical process flow of an order beingdelivered, according to one embodiment.

FIG. 61A is a view of a neighborhood flying football, according to oneembodiment.

FIG. 61B is a view of a neighborhood flying football being controlled bya user, according to one embodiment.

Other features of the present embodiments will be apparent from theaccompanying drawings and from the detailed description that follows.

DETAILED DESCRIPTION

A method, apparatus, and system of multi-occupant structure in ageo-spatial environment are disclosed. In the following description, forthe purposes of explanation, numerous specific details are set forth inorder to provide a thorough understanding of the various embodiments. Itwill be evident, however, to one skilled in the art that the variousembodiments may be practiced without these specific details.

A method, device and system of an autonomous neighborhood multi-coptercommerce network in a community are disclosed. In one embodiment, anautonomous neighborhood multi-copter includes a storage compartment ofthe autonomous neighborhood multi-copter in which items are storable, acomputer system of the autonomous neighborhood multi-copter that iscommunicatively coupled to a commerce server of a neighborhoodcommunication system through a wireless network to autonomously navigatethe autonomous neighborhood multi-copter to a destination in theneighborhood specified by the commerce server using a peer-to-peernetwork of client side devices in the neighborhood that aregeo-constrained to a location of a defined neighborhood, and anavigation server of the autonomous neighborhood multi-copter to providea remote sensing capability to the autonomous neighborhood multi-coptersuch that the autonomous neighborhood multi-copter is autonomouslynavigable to the destination using the peer-to-peer network.

FIG. 1A shows an autonomous neighborhood multi-copter. Particularly,FIG. 1A shows the autonomous neighborhood multi-copter 100, a storagecompartment 101, a sensor system 102, a user interface 104, anelectronic locking mechanism 106, a telescoping platform 107, a pathlighting device 108, a foldable all-terrain wheels 109, an ejectionmodule 110, a sidewalk detection sensor 111, and a propellers 113. Inone embodiment, may be an electric and/or battery powered device. Apropulsion system 208 (shown in FIG. 2) of the autonomous neighborhoodmulti-copter 100 (e.g., driverless delivery vehicle, autonomousneighborhood delivery rover) may be powered by solar and/or wind power,according to one embodiment. In one embodiment, the autonomousneighborhood multi-copter may be a wheeled vehicle, a treaded vehicle,an aerial vehicle, an aquatic vehicle, and/or a hybrid terrain vehicle(e.g., one capable of transitioning between air, land, and/or water).

The autonomous neighborhood multi-copter 100 may comprise of a set ofwheels aligned in a way to provide the autonomous neighborhoodmulti-copter 100 (e.g., neighborhood rover vehicle) stability whentraveling to and/or from destinations (e.g., on sidewalks, bike lanes, aroadway, over rocks, over grass). The storage compartment 101 may be anyshape that enables the autonomous neighborhood multi-copter 100 toadequately store desired item(s) 4502 (e.g., a rectangular shape, aspherical shape, a cone shape). The storage compartment 101 may be madeof metallic materials, wood, and/or a polymer based material. Theinterior of the storage compartment may be temperature controlled viathe temperature control module 246 (e.g., heated, cooled, kept at acertain humidity) and/or may be comprised of (e.g., be made of, linedwith, reinforced with, padded with) materials to aid in transport and/orstorage of items 4502. In one embodiment, the storage compartment 101may be lined with vinyl, nylon and/or Cordura to aid in keeping contentsheated. In another embodiment, the storage compartment 101 may be paddedand/or be equipped with a suspensions system to protect fragilecontents. The contents may be a gastronomical item, a perishable item, aretail good, an electronic device, a piece of mail, an organ (e.g., formedical use), and/or any item capable of being transported via theautonomous neighborhood multi-copter 100.

The storage compartment 101 may have compartments (e.g., separatesections capable of being maintained at different temperatures and/orhumidity, trays, compartmentalized areas) and/or may have separateopenings on the surface of the storage compartment 101 for eachcompartment(s). The autonomous neighborhood multi-copter 100 maycomprise of an ejection module 110, according to one embodiment. Theejection module 110 may be communicatively couple with a camera (e.g., aseparate camera from that of a sensor system 102) and/or may eject items4502 (e.g., packages, letters, non-fragile items) from the storagecompartment 101 using pressurized air. In one embodiment, the autonomousneighborhood multi-copter 100 may be able to eject items 4502 in aspecific compartment of the storage compartment 101 while not ejectingitems 4502 in another compartment and/or keeping other items 4502controlled at a certain temperature and/or humidity.

In one embodiment, the sensor system 102 may be comprised of severalsensors (e.g., several types, several of the same kind). The autonomousneighborhood multi-copter 100 may possess multiple sensor systems 102.The sensor system 102 may be physically associated with the autonomousneighborhood multi-copter 100 so that the vehicle is able to captureand/or analyze its surrounding environment and/or navigate. The sensorsystem 102 may be comprised of a global positioning system 218, aninternal measurement unit 220, a radar unit 222, a laserrangefinder/LIDAR unit 224, a camera 226, and/or an ultrasound unit 228(e.g., as described in FIG. 2).

The autonomous neighborhood multi-copter 100 may have a user interface104 physically associated with it. The user interface 104 may be a touchscreen system, a key-pad based system, an audio based system (e.g.,voice command), etc. The user interface 104 may enable individuals(e.g., a user of the autonomous neighborhood multi-copter 100) to entercommands (e.g., a destination, a set of details about the pick-up and/ordrop-off, a set of constraints for the vehicle's operation). In oneembodiment, the user interface 104 may require a user verification(e.g., passcode, voice recognition, a biometric scan) before access tothe user interface 104 may be granted. In another embodiment, the userinterface 104 may be covered and/or encased by a protective surfaceuntil activated (e.g., unlocked) for use.

An electronic locking mechanism 106 may be physically associated withthe autonomous neighborhood multi-copter 100, according to oneembodiment. The electronic locking mechanism 106 may be a combinationlock, an electronic lock, a signal based lock, a passcode lock, abiometric scanner (e.g., fingerprint reader) and/or may keep thecontents of the autonomous neighborhood multi-copter 100 secure. In oneembodiment, the electronic locking mechanism 106 may be unlocked and/orlocked via the user interface 104. In one embodiment, the electroniclocking mechanism 106 may automatically unlock when the autonomousneighborhood multi-copter 100 arrives at its destination. The electroniclocking mechanism 106 may unlock when the sender (e.g., owner, user) ofthe autonomous neighborhood multi-copter 100 remotely unlocks theelectronic locking mechanism 106 (e.g., using a data processing system4204 (e.g., a smart phone, a tablet, a mobile device, a computer, alaptop). In another embodiment, a passcode may be sent to the recipient(e.g., store, individual, company) (e.g., via text message, via a pushnotification, via an update on a profile, in an email, etc.). Thepasscode to the electronic locking mechanism 106 may be changed on apredetermined basis (e.g., with every use, daily, weekly, hourly, uponrequest of the owner, upon request of the user (e.g., sender)). In oneembodiment, the electronic locking mechanism 106 may be unlocked using anear-field communication technology such as iBeacon, NFC and/or a keypadunlock code.

The path lighting device 108 of the autonomous neighborhood multi-copter100 may automatically active a set of light emitting diodes encompassingthe autonomous neighborhood multi-copter 100 when a light sensor detectsthat an environmental brightness is below a threshold lumens. The pathlighting device 108 may be comprised of multiple light sources. Theautonomous neighborhood multi-copter 100 may have multiple path lightingdevices 108.

The autonomous neighborhood multi-copter 100 may have all terrain wheels109. The all terrain wheels 109 may be shock absorbing, on/off road,airless, puncture-sealing, run-flat etc. The all-terrain wheels 109 maybe foldable (e.g., capable of being folded, retracted, and/or stored insuch a way to enable optimal air travel). The propellers 113 may becomprised of metallic, rubber, polymer material and/or any othermaterial known in the art. The propellers 113 may be constructed and/oraligned in such a way as to enable the autonomous neighborhoodmulti-copter 100 to have stability in flight and/or transport (e.g.,carry, support and/or hold) the items it carries. The autonomousneighborhood multi-copter 100 may have a sidewalk detection sensor 111to provide a mechanism through which the autonomous neighborhoodmulti-copter is able to detect a gradation ride caused by a sidewalkstart location and a gradation drop caused by a sidewalk end location(e.g., curb). The sidewalk detection sensor 111 may be a LIDAR, a RADAR,a setero optical sensor, an ultrasound unit 228, and/or another type ofsensor. The telescoping platform 107 may enable the autonomousneighborhood multi-copter 100 to traverse the sidewalk (e.g., move fromthe sidewalk to the road (e.g., bike lane) and/or from the road to thesidewalk) without disturbing, damaging and/or shifting its contents. Thetelescoping platform 107 is better described in FIGS. 43A and 43 b.

In one embodiment, the autonomous neighborhood multi-copter 100 may havemobile network capabilities and/or WiFi capabilities. The autonomousneighborhood multi-copter 100 may have built in 2G, 3G, 4G etc. cellularcapabilities. Users may be able to activate the mobile networkcapability (e.g., 4G cellular capability) if, for example, they wish totake the autonomous neighborhood multi-copter 100 beyond the range oftheir WiFi access point. If the user elects to activate this feature,they may pay a fee (e.g., a monthly fee, an annual fee, a per minutefee, a fee per unit or data) to the geospatially constrained socialnetwork 4242 (e.g., Fatdoor.com). This way, the user may not be requiredto contact the mobile carrier or alter their existing mobile plan. Theuser may be able to stop (e.g., turn off, deactivate, and/or suspend)the service using a data processing system (e.g., the data processingsystem 4204 shown in FIG. 42).

FIG. 1B is a neighborhood view 151 of the autonomous neighborhoodmulti-copter 100 traveling along a flight path in an environment of theautonomous neighborhood multi-copter 152. Particularly, FIG. 1B shows asidewalk 112, a roadway 114, a claimable residential addresses 115, anenvironmental brightness 117, a set of weather conditions 119, and aflight path 120. In one embodiment, the autonomous neighborhoodmulti-copter 100 may travel along the flight path 120. FIG. 1B alsoshows an autonomous neighborhood multi-copter 100B traveling on asidewalk while making a delivery, according to one embodiment. Theautonomous neighborhood multi-copter (e.g., the autonomous neighborhoodmulti-copter 100B) may travel on sidewalks 112, bike lanes 304, and/orroadways 114. These paths, along with other possible routes of travelthrough the neighborhood, may be mapped (e.g., input to the globalpositioning system 218, input to the computer system 200, bytransporting the autonomous neighborhood multi-copter 100 through theneighborhood previously in order to create a map via the sensor system102) on and/or by the autonomous neighborhood multi-copter 100. Theaerial space of the neighborhood may also be mapped (e.g., using FAArules and/or regulations, flight path data compiled from multipleautonomous neighborhood multi-copters 100, and/or accounting for theelevation of markers (e.g., trees, telephone poles, power lines, and/orbuildings) in the neighborhood. In this embodiment, the autonomousneighborhood multi-copter can both fly and traverse land (e.g., whenbattery is low and when conditions warrant).

In one embodiment, the sidewalk detection sensor 111 may scan the pathof the autonomous neighborhood multi-copter 100 and may detect that thesidewalk 112 is ending. The telescoping platform 107 may allow anynumber of the autonomous neighborhood multi-copter's 100 wheels to belowered and/or raised independent of the other wheels. In oneembodiment, as the autonomous neighborhood multi-copter 100 approachedthe end of a sidewalk 112, the front set of wheels may by lowered offthe curb to meet the roadway 114 below as the rear wheels remain on thesidewalk 112. The rear set of wheels may then be lowered from thesidewalk 112 to the roadway 114 as the autonomous neighborhoodmulti-copter 100 moves from the sidewalk 112 to the roadway 114. Oncethe autonomous neighborhood multi-copter 100 is completely on theroadway 114, all wheels may be returned to their original positions.This way, the autonomous neighborhood multi-copter 100 may be able toseamlessly transition from the roadway 114 to the sidewalk 112 and/orfrom the sidewalk 112 to the roadway 114.

FIG. 2 is a functional block diagram 250 illustrating an autonomousneighborhood multi-copter, according to an example embodiment. Theautonomous neighborhood multi-copter 100 could be configured to operatefully or partially in an autonomous mode. For example, the autonomousneighborhood multi-copter 100 could control itself while in theautonomous mode, and may be operable to determine a current state of thevehicle and its environment, determine a predicted behavior of at leastone other entity (e.g., a plane, a vehicle, a pedestrian, a biker, ananimal) in the environment, determine a confidence level that maycorrespond to a likelihood of the at least one other vehicle to performthe predicted behavior, and/or control the autonomous neighborhoodmulti-copter 100 based on the determined information (described in FIGS.3A-C). While in autonomous mode, the autonomous neighborhoodmulti-copter 100 may be configured to operate without human interaction.

The autonomous neighborhood multi-copter 100 could include varioussubsystems such as a computer system 200, a propulsion system 208, asensor system 102, a control system 230, one or more peripherals 248, aswell as a power supply 258. The autonomous neighborhood multi-copter 100may include more or fewer subsystems and each subsystem could includemultiple elements. Further, each of the subsystems and elements ofautonomous neighborhood multi-copter 100 could be interconnected. Thus,one or more of the described functions of the autonomous neighborhoodmulti-copter 100 may be divided up into additional functional orphysical components, or combined into fewer functional or physicalcomponents. In some further examples, additional functional and/orphysical components may be added to the examples illustrated by FIG. 2.

The propulsion system 208 may include components operable to providepowered motion for the autonomous neighborhood multi-copter 100.Depending upon the embodiment, the propulsion system 208 could includethe propellers 113, an engine/motor 210, an energy source 212, atransmission 214, and/or wheels/tires 216 (e.g., the wheels 109). Theengine/motor 210 could be any combination of an internal combustionengine, an electric motor, steam engine, Stirling engine, a solarpowered engine, or other types of engines and/or motors. In someembodiments, the engine/motor 210 may be configured to convert energysource 212 into mechanical energy. In some embodiments, the propulsionsystem 208 could include multiple types of engines and/or motors. Forinstance, a gas-electric hybrid vehicle could include a gasoline engineand an electric motor. Other examples are possible. In one embodiment,separate engine/motors 210 may be used to propel the wheels 109 and thepropellers 113. In another embodiment, the engine/motor 210 may propelboth the wheels 109 and the propellers 113.

The energy source 212 could represent a source of energy that may, infull or in part, power the engine/motor 210. That is, the engine/motor210 could be configured to convert the energy source 212 into mechanicalenergy. Examples of energy sources 212 include gasoline, diesel, otherpetroleum-based fuels, propane, other compressed gas-based fuels,ethanol, solar panels, batteries, and other sources of electrical power.The energy source(s) 212 could additionally or alternatively include anycombination of fuel tanks, batteries, capacitors, and/or flywheels. Theenergy source 212 could also provide energy for other systems of theautonomous neighborhood multi-copter 100. In one embodiment, separateenergy sources 212 and/or power supplies 258 may power the wheels 109and propellers 113. In another embodiment, the wheels 109 and propellers113 may use the same power supply 258 and/or energy source 212.

The transmission 214 could include elements that are operable totransmit mechanical power from the engine/motor 210 to the propellers109 and/or wheels/tires 216. To this end, the transmission 214 couldinclude a gearbox, clutch, differential, and drive shafts. Thetransmission 214 could include other elements. The drive shafts couldinclude one or more axles that could be coupled to the one or morepropeller 109 and/or wheels/tires 216. In one embodiment, multipletransmissions 214 may be used to operate the propellers 113 and/orwheels 109.

The wheels/tires 216 of autonomous neighborhood multi-copter 100 couldbe configured in various formats, including a unicycle,bicycle/motorcycle, tricycle, or a four-wheel format, a treaded system.Other wheel/tire geometries are possible, such as those including six ormore wheels. Any combination of the wheels/tires 216 of autonomousneighborhood multi-copter 100 may be operable to rotate differentiallywith respect to other wheels/tires 216. The wheels/tires 216 couldrepresent at least one wheel that is fixedly attached to thetransmission 214 and at least one tire coupled to a rim of the wheelthat could make contact with the driving surface. The wheels/tires 216could include any combination of metal and rubber, or anothercombination of materials. In one embodiment, the wheels/tires 216 and/orpropellers 109 may include a propeller/wheel encoding sensor 223.

The propellers 113 of autonomous neighborhood multi-copter 100 could beconfigured in various formats, including a single propeller, abi-propeller configuration, a three propeller configuration, aconfiguration similar to that of a helicopter, or a four-wheel format, atreaded system. Other propeller 113 geometries are possible, such asthose including six or more propellers. Any combination of thepropellers 113 of autonomous neighborhood multi-copter 100 may beoperable to rotate differentially with respect to other propellers 113.The propellers 113 could represent at least one propeller that isfixedly attached to the transmission 214 and at least propeller 113coupled to a rim of the propeller 113 that could make contact with thedriving surface. The propellers 113 could include any combination ofmetal and rubber, or another combination of materials. In oneembodiment, the wheels/tires 216 and/or propellers 113 may include apropeller/wheel encoding sensor 223.

The sensor system 102 may include a number of sensors configured tosense information about the environment of the autonomous neighborhoodmulti-copter 152. For example, the sensor system 102 could include aGlobal Positioning System (GPS) 218, an accelerometer sensor 219, aninertial measurement unit (IMU) 220, a gyroscopic sensor 221, a RADARunit 222, a propeller/wheel encoding sensor 223, a laserrangefinder/LIDAR unit 224, a compass sensor 225, a camera 226, a stereooptical sensor 227, and/or an ultrasound unit 228. The sensor system 102could also include sensors configured to monitor internal systems of theautonomous neighborhood multi-copter 100 (e.g., O.sub.2 monitor, fuelgauge, engine oil temperature). Other sensors are possible as well. Oneor more of the sensors included in sensor system 102 could be configuredto be actuated separately and/or collectively in order to modify aposition and/or an orientation of the one or more sensors.

The GPS 218 may be any sensor configured to estimate a geographiclocation of the autonomous neighborhood multi-copter 100. To this end,GPS 218 could include a transceiver operable to provide informationregarding the position of the autonomous neighborhood multi-copter 100with respect to the Earth. In one embodiment, the GPS 218 may becommunicatively coupled with the commerce server 4200 allowing a stateof the autonomous neighborhood multi-copter 100 and/or a location of theautonomous neighborhood multi-copter to be relayed to the server. In oneembodiment, GPS 218 may be physically associated with the autonomousneighborhood multi-copter 100 so that the vehicle is able toperiodically (e.g., continuously, every minute, at a predeterminedpoint) communicate its location to the garage sale server through anetwork 2904 and/or a cellular network 4208. In one embodiment, theglobal positioning system 218 may be communicatively coupled with theprocessor 202, a memory (e.g., the data storage 204), the LIDAR unit224, the RADAR 222, and/or the camera 226.

The IMU 220 could include any combination of sensors (e.g.,accelerometers and gyroscopes) configured to sense position andorientation changes of the autonomous neighborhood multi-copter 100based on inertial acceleration. In one embodiment, the IMU 220 may beused to calculate the magnitude of deceleration.

The RADAR unit 222 may represent a system that utilizes radio signals tosense objects within the local environment of the autonomousneighborhood multi-copter 152. In some embodiments, in addition tosensing the objects, the RADAR unit 222 may additionally be configuredto sense the speed and/or heading of the objects. The RADAR unit 222 maydetermine a range, an altitude, a direction, a shape, and/or speed ofobjects. In one embodiment, the autonomous neighborhood multi-copter 100may be able to travel on sidewalks, bike lanes, the side of the road, instreams, rivers, and/or may be able to stop at stop lights, wait tocross the road, navigate vehicle and/or pedestrian traffic, obey trafficlaws etc. The autonomous neighborhood multi-copter 100 may have upon itinfrared sensors, laser sensors and/or an on board navigation.

Similarly, the laser rangefinder or LIDAR unit 224 may be any sensorconfigured to sense objects in the environment in which the autonomousneighborhood multi-copter 100 is located using lasers. Depending uponthe embodiment, the laser rangefinder/LIDAR unit 224 could include oneor more laser sources, a laser scanner, and one or more detectors, amongother system components. The laser rangefinder/LIDAR unit 224 could beconfigured to operate in a coherent (e.g., using heterodyne detection)or an incoherent detection mode. The LIDAR 108 may use ultraviolet,visible and/or near infrared light to image objects in a 360 degreefield of view. The objects imaged by the LIDAR 108 may includenon-metallic objects, metallic objects, rocks, people, vehicles, rain,traffic cones, traffic lights and/or signs etc. The LIDAR 108 may becommunicatively couple to the navigation server to provide remotesensing capability to the autonomous neighborhood multi-copter 100 suchthat the autonomous neighborhood multi-copter 100 is autonomously (E.g.,and/or pilotlessly) navigable to the destination.

The camera 226 could include one or more devices configured to capture aplurality of images of the environment of the autonomous neighborhoodmulti-copter 152. The camera 226 could be a still camera or a videocamera. The camera 226 may be a set of cameras, a singlemultidirectional camera, a camera with a 360 degree view, a rotatingcamera, a stereo optic camera etc. The control system 230 may beconfigured to control operation of the autonomous neighborhoodmulti-copter 100 and its components. Accordingly, the control system 230could include various elements include steering unit 232, throttle 234,deceleration unit 236, a sensor fusion algorithm 238, a computer visionsystem 240, a navigation server 242, an obstacle avoidance system 244, atemperature control module 246, and an air control system 247. In oneembodiment, the air control system 247 may be used to navigate theautonomous neighborhood multi-copter 100 while in aerial mode (e.g., aseparate mode from land based travel).

The steering unit 232 could represent any combination of mechanisms thatmay be operable to adjust the heading (e.g., directional heading and/orthe altitude) of autonomous neighborhood multi-copter 100. The throttle234 could be configured to control, for instance, the operating speed ofthe engine/motor 210 and, in turn, control the speed of the autonomousneighborhood multi-copter 100. The deceleration unit 236 could includeany combination of mechanisms configured to decelerate the autonomousneighborhood multi-copter 100. The deceleration unit 236 could usefriction to slow the wheels/tires 216. In other embodiments, thedeceleration unit 236 could convert the kinetic energy of thewheels/tires 216 to electric current. The deceleration unit 236 may takeother forms as well. In one embodiment, the deceleration unit 236 mayslow the air born autonomous neighborhood multi-copter 100 by deployingflaps and/or reversing the direction of motion (e.g., reversing thepropeller direction and/or orientation to propel the multi-copter in theopposite direction thereby slowing the current velocity of motion). Thesensor fusion algorithm 238 may be an algorithm (or a computer programproduct storing an algorithm) configured to accept data from the sensorsystem 102 as an input. The data may include, for example, datarepresenting information sensed at the sensors of the sensor system 102.The sensor fusion algorithm 238 could include, for instance, a Kalmanfilter, Bayesian network, or other algorithm. The sensor fusionalgorithm 238 could further provide various assessments based on thedata from sensor system 102. Depending upon the embodiment, theassessments could include evaluations of individual objects and/orfeatures in the environment of autonomous neighborhood multi-copter 100,evaluation of a particular situation, and/or evaluate possible impactsbased on the particular situation. In one embodiment, the sensor fusionalgorithm may determine that a sidewalk is ending and/or beginning(e.g., by sensing a curb). The autonomous neighborhood multi-copter maybe able to adjust its path to avoid and/or intersect with the curband/or sidewalk (e.g., traversing the curb to move from a bike lane to asidewalk or vice versa). Other assessments are possible. The autonomousneighborhood multi-copter 100 may be able to use the sensor fusionalgorithm 238 to use multiple sources of data to navigate intersections(e.g., while turning in an intersection) without use of lanes, paintedlines, demarcated paths etc. This may be especially useful for aerialtravel.

The computer vision system 240 may be any system operable to process andanalyze images captured by camera 226 in order to identify objectsand/or features in the environment of autonomous neighborhoodmulti-copter 100 that could include traffic signals, road wayboundaries, and obstacles. The computer vision system 240 could use anobject recognition algorithm, a Structure From Motion (SFM) algorithm,video tracking, and other computer vision techniques. In someembodiments, the computer vision system 240 could be additionallyconfigured to map an environment, track objects, estimate the speed ofobjects, etc. The navigation and pathing system 242 may be any systemconfigured to determine a flight and/or driving path for the autonomousneighborhood multi-copter 100. The navigation and pathing system 242 mayadditionally be configured to update the driving path dynamically whilethe autonomous neighborhood multi-copter 100 is in operation. In someembodiments, the navigation and pathing system 242 could be configuredto incorporate data from the sensor fusion algorithm 238, the GPS 218,and one or more predetermined maps so as to determine the driving pathfor autonomous neighborhood multi-copter 100. The obstacle avoidancesystem 244 could represent a control system configured to identify,evaluate, and avoid or otherwise negotiate potential obstacles (e.g.,tree tops, buildings, pedestrians, vehicles, bicycles, sidewalks (e.g.,curbs, paved sidewalks), traffic cones, downed tree branches) in theenvironment of the autonomous neighborhood multi-copter 152. The controlsystem 230 may additionally or alternatively include components otherthan those shown and described.

Peripherals 248 may be configured to allow interaction between theautonomous neighborhood multi-copter 100 and external sensors, othervehicles, other computer systems, and/or a user. For example,Peripherals 248 could include a wireless communication system 251, theuser interface 104, a microphone 254, a speaker 256, the path lightingdevice 108, and/or the ejection module 110. The path lighting device mayinclude a set of light emitting diodes 270 and/or a light sensor 272 todetect that an environmental brightness is below a threshold luminosityThe speaker 1352 may play a message recorded (e.g., through themicrophone 254 and/or a mobile device and/or computer that sends themessage to the autonomous neighborhood multi-copter). The microphone 254may pick up and/or record noise from the autonomous neighborhoodmulti-copter's environment. The speaker 256 may play the message (e.g.,instructions to an individual at a destination (e.g., an order)) and/orannounce actions of the autonomous neighborhood multi-copter 100 (e.g.,announce that the autonomous neighborhood multi-copter 100 is about tomake a left turn and/or break). In one embodiment, the autonomousneighborhood multi-copter 100 may have one or more turn signals and/orbreak lights.

The speaker 256, microphone 254, and/or the wireless communicationsystem 251 (e.g., working in concert) may record and/or play an audiomessage (e.g., from the sender to the recipient and/or vice versa)recorded on the autonomous neighborhood multi-copter 100 itself and/orsent to the autonomous neighborhood multi-copter 100 from the commerceserver 4200 through the network. The wireless communication system 251may enable the autonomous neighborhood multi-copter 100 to communicatethrough the network with other autonomous neighborhood multi-copters 100(e.g., in the network, within a threshold radial distance 4219, owned bythe same owner, sent by the same sender, sent to the same recipient). Inone embodiment, this communication may be used to maximize efficiency ofroutes, coordinate and/or ensure timely delivery, to form a convoy etc.

In an example embodiment, the Peripherals 248 could provide, forinstance, means for a user of the autonomous neighborhood multi-copter100 to interact with the user interface 104. To this end, the userinterface 104 could provide information to a user of autonomousneighborhood multi-copter 100. The user interface 104 could also beoperable to accept input from the user via a touchscreen. Thetouchscreen may be configured to sense at least one of a position and amovement of a user's finger via capacitive sensing, resistance sensing,or a surface acoustic wave process, among other possibilities. Thetouchscreen may be capable of sensing finger movement in a directionparallel or planar to the touchscreen surface, in a direction normal tothe touchscreen surface, or both, and may also be capable of sensing alevel of pressure applied to the touchscreen surface. The touchscreenmay be formed of one or more translucent or transparent insulatinglayers and one or more translucent or transparent conducting layers. Thetouchscreen may take other forms as well.

In other instances, the Peripherals 248 may provide means for theautonomous neighborhood multi-copter 100 to communicate with deviceswithin its environment. The microphone 254 may be configured to receiveaudio (e.g., a voice command or other audio input) from a user of theautonomous neighborhood multi-copter 100. Similarly, the speakers 256may be configured to output audio to the user of the autonomousneighborhood multi-copter 100. The ejection module 110 may be coupledwith a camera and/or may enable the autonomous neighborhood multi-copter100 to eject item(s) 4502 using pressurized air (e.g., deliver packagesto a door step without leaving the air or sidewalk 112).

In one example, the wireless communication system 251 could beconfigured to wirelessly communicate with one or more devices directlyor via a communication network. For example, wireless communicationsystem 251 could use 3G cellular communication, such as CDMA, EVDO,GSM/GPRS, or 4G cellular communication, such as WiMAX or LTE.Alternatively, wireless communication system 251 could communicate witha wireless local area network (WLAN), for example, using WiFi. In someembodiments, wireless communication system 251 could communicatedirectly with a device, for example, using an infrared link, Bluetooth,or ZigBee. Other wireless protocols, such as various vehicularcommunication systems, are possible within the context of thedisclosure. For example, the wireless communication system 251 couldinclude one or more dedicated short range communications (DSRC) devicesthat could include public and/or private data communications betweenvehicles and/or roadside stations. The wireless communication system 251may also enable the autonomous neighborhood multi-copter 100 tocommunicate and/or coordinate with other autonomous neighborhoodmulti-copters 100.

The power supply 258 may provide power to various components ofautonomous neighborhood multi-copter 100 and could represent, forexample, a rechargeable lithium-ion, lithium-sulfur, or lead-acidbattery. In some embodiments, one or more banks of such batteries couldbe configured to provide electrical power. Other power supply materialsand configurations are possible. In some embodiments, the power supply258 and energy source 212 could be implemented together, as in someall-electric cars. In one embodiment, the autonomous neighborhoodmulti-copter 100 may autonomously direct itself to a charging station(e.g., a set non-transitory charging stations, a nearest chargingstation, a nearest preapproved (e.g., claimed) charging station) and/orconduct necessary operations to charge itself when an energy supplyreaches a threshold level, at a certain time of day, when a certainamount of time has elapsed, when a certain distance has been traveledetc.

Many or all of the functions of autonomous neighborhood multi-copter 100(e.g., the autonomous neighborhood multi-copter 100B) could becontrolled by computer system 200. Computer system 200 may include atleast one processor 202 (which could include at least onemicroprocessor) that executes instructions 206 stored in anon-transitory computer readable medium, such as the data storage 204.The processor 202 may be communicatively coupled to the commerce server4200 (shown in FIG. 42) of the neighborhood communication system 2950through a wireless network (e.g., the network of FIG. 42) toautonomously navigate the autonomous neighborhood multi-copter (e.g.,the neighborhood rover vehicle) to a destination specified by thecommerce server 4200. The computer system 200 may also represent aplurality of computing devices that may serve to control individualcomponents or subsystems of the autonomous neighborhood multi-copter 100in a distributed fashion.

In some embodiments, data storage 204 may contain instructions 206(e.g., program logic) executable by the processor 202 to execute variousfunctions of autonomous neighborhood multi-copter 100, including thosedescribed above in connection with FIG. 2. Data storage 204 may containadditional instructions as well, including instructions to transmit datato, receive data from, interact with, and/or control one or more of thepropulsion system 208, the sensor system 102, the control system 230,and the Peripherals 248. In addition to the instructions 206, the datastorage 204 may store data such as air space maps, roadway maps, pathinformation, among other information. Such information may be used bythe autonomous neighborhood multi-copter 100 and computer system 200 atduring the operation of the autonomous neighborhood multi-copter 100 inthe autonomous, semi-autonomous, and/or manual modes. The autonomousneighborhood multi-copter 100 may include a user interface 104 forproviding information to or receiving input from a user of theautonomous neighborhood multi-copter 100. The user interface 104 couldcontrol or enable control of content and/or the layout of interactiveimages that could be displayed on the touchscreen. Further, the userinterface 104 could include one or more input/output devices within theset of Peripherals 248, such as the wireless communication system 251,the user interface 104, the microphone 254, and the speaker 256.

The computer system 200 may control the function of the autonomousneighborhood multi-copter 100 based on inputs received from varioussubsystems (e.g., propulsion system 208, sensor system 102, and controlsystem 230), as well as from the user interface 104. For example, thecomputer system 200 may utilize input from the control system 230 inorder to control the steering unit 232 to avoid an obstacle detected bythe sensor system 102 and the obstacle avoidance system 244. Dependingupon the embodiment, the computer system 200 could be operable toprovide control over many aspects of the autonomous neighborhoodmulti-copter 100 and its subsystems. The components of autonomousneighborhood multi-copter 100 could be configured to work in aninterconnected fashion with other components within or outside theirrespective systems. For instance, in an example embodiment, the camera226 could capture a plurality of images that could represent informationabout a state of an environment of the autonomous neighborhoodmulti-copter 152 operating in an autonomous mode. The environment couldinclude another vehicle. The computer vision system 240 could recognizethe other vehicle as such based on object recognition models stored indata storage 204.

The computer system 200 could carry out several determinations based onthe information. For example, the computer system 200 could determineone or more predicted behaviors 305 of the other vehicle. The predictedbehavior could be based on several factors including the current stateof the autonomous neighborhood multi-copter 100 (e.g., multi-copterspeed, current lane, etc.) and the current state of the environment ofthe autonomous neighborhood multi-copter 152 (e.g., speed limit, numberof available lanes, position and relative motion of other vehicles,etc.). For instance, in a first scenario in which the autonomousneighborhood vehicle 100 is traveling on land, if another vehicle israpidly overtaking the autonomous neighborhood multi-copter 100 from aleft-hand lane, while autonomous neighborhood multi-copter 100 is in acenter lane, one predicted behavior could be that the other vehicle willcontinue to overtake the autonomous neighborhood multi-copter 100 fromthe left-hand lane.

In a second scenario, if the other vehicle is overtaking autonomousneighborhood multi-copter 100 in the left-hand lane, but a third vehicletraveling ahead of autonomous neighborhood multi-copter 100 is impedingfurther progress in the left-hand lane, a predicted behavior could bethat the other vehicle may cut in front of autonomous neighborhoodmulti-copter 100. The computer system 200 could further determine aconfidence level corresponding to each predicted behavior. For instance,in the first scenario, if the left-hand lane is open for the othervehicle to proceed, the computer system 200 could determine that it ishighly likely that the other vehicle will continue to overtakeautonomous neighborhood multi-copter 100 and remain in the left-handlane. Thus, the confidence level corresponding to the first predictedbehavior (that the other vehicle will maintain its lane and continue toovertake) could be high, such as 90%.

In the second scenario, where the other vehicle is blocked by a thirdvehicle, the computer system 200 could determine that there is a 50%chance that the other vehicle may cut in front of autonomousneighborhood multi-copter 100 since the other vehicle could simply slowand stay in the left-hand lane behind the third vehicle. Accordingly,the computer system 200 could assign a 50% confidence level (or anothersignifier) to the second predicted behavior in which the other vehiclemay cut in front of the autonomous neighborhood multi-copter 100.

In the example embodiment, the computer system 200 could work with datastorage 204 and other systems in order to control the control system 230based on at least on the predicted behavior, the confidence level, thecurrent state of the autonomous neighborhood multi-copter 100, and thecurrent state of the environment of the autonomous neighborhoodmulti-copter 152. In the first scenario, the computer system 200 mayelect to adjust nothing as the likelihood (confidence level) of theother vehicle staying in its own lane is high. In the second scenario,the computer system 200 may elect to control autonomous neighborhoodmulti-copter 100 to slow down slightly (by reducing throttle 234) or toshift slightly to the right (by controlling steering unit 232) withinthe current lane in order to avoid a potential collision. Other examplesof interconnection between the components of autonomous neighborhoodmulti-copter 100 are numerous and possible within the context of thedisclosure.

Although FIG. 2 shows various components of autonomous neighborhoodmulti-copter 100, i.e., wireless communication system 251, computersystem 200, data storage 204, and user interface 104, as beingintegrated into the autonomous neighborhood multi-copter 100, one ormore of these components could be mounted or associated separately fromthe autonomous neighborhood multi-copter 100. For example, data storage204 could, in part or in full, exist separate from the autonomousneighborhood multi-copter 100. Thus, the autonomous neighborhoodmulti-copter 100 could be provided in the form of device elements thatmay be located separately or together. The device elements that make upautonomous neighborhood multi-copter 100 could be communicativelycoupled together in a wired and/or wireless fashion.

In one embodiment, the autonomous neighborhood multi-copter 100 may havea flight recorder module 249. While not shown in FIG. 2, it should beappreciated that the flight recorder module 249 may be included as partof the computer system 200, the control system 230, the peripherals 248and/or any other system in the autonomous neighborhood multi-copter 100.In one embodiment, the flight recorder module 249 may not be included inthe above mentioned system(s) and/or may be a USB dongle which attachesto the autonomous neighborhood multi-copter 100. The flight module 249may add data storage to the multi-copter (e.g., 4 GB of storage) and/orGPS tracking and/or navigation. In one embodiment, the flight recordermodule's 249 GPS tracking and/or navigation may be the globalpositioning system 218 and/or navigation server 242. In one embodiment,the global positioning system 218 and/or navigation server 242 may beseparate from the flight recorder module 249. The flight recorder module249 may allow pilots (e.g., users of the autonomous neighborhoodmulti-copter 100) to define the flight path 120 by selecting a series ofwaypoints that the autonomous neighborhood vehicle 100 will follow. Inone embodiment, the user may be able to create their own flight plans(e.g., flight paths 120) with multiple intermediate points in 3D thatthe autonomous neighborhood multi-copter 100 will automatically follow.

In one embodiment, the flight recorder module 249 may record flightsettings (e.g., up to 350 flight settings) and/or may act as a “blackbox” for the autonomous neighborhood multi-copter 100. In oneembodiment, the autonomous neighborhood multi-copter 100 may be fullyand/or partially autonomous and/or be able to switch between autonomousand/or non-autonomous (e.g., partially autonomous and/or non-autonomous)modes. The flight recorder module 249 may record flights and/or videosusing flash memory (e.g., 4 GB flash memories). Users may be able toreview their flights (e.g., from different angles) modeled in 3D on amap displayed on the data processing system 104. In one embodiment, thestability of the autonomous neighborhood multi-copter 100 in flightand/or on land may be improved using the flight recorder module's 249GPS sensors.

FIG. 3A illustrates a scenario 350 involving bike lane 307 a flight lane304A and 304B. An autonomous neighborhood multi-copter 100C (e.g., anautonomous neighborhood aerial vehicle 4300 shown in FIG. 43A) could bein the bike lane 307 flight lane 304B along with a bird. An autonomousneighborhood multi-copter 100 could be operating in an autonomous modein the flight lane 304A. In one embodiment, the autonomous neighborhoodmulti-copter 100 may have the ability to travel autonomously in a bikelane 307 flight lane 304A. The autonomous neighborhood multi-copter 100and the autonomous neighborhood multi-copter 100C could be travelling atthe same speed. A bird 302A could be in the flight lane 304B (e.g., apredetermined area surrounding the flight path of the entity) andapproaching the autonomous neighborhood multi-copter 100C from behind ata higher rate of speed. The sensor system 102 (e.g., the LIDAR 108, theRADAR unit 222, the camera 226, an ultrasound unit 228) of theautonomous neighborhood multi-copter 100 could be capturing sensor databased on an environment of the autonomous neighborhood multi-copter 100.

Although in the embodiment of FIG. 3A, the sensor system 102 is shown onthe top of the autonomous neighborhood multi-copter 100, it should beappreciated that the sensor system 102 may be located internally, on thefront, on the sides etc. of the autonomous neighborhood multi-copter100. In particular, the camera 226 could capture a plurality of imagesof the autonomous neighborhood multi-copter 100C, the other bird 302A,as well as other features in the environment so as to help the computersystem of the autonomous neighborhood multi-copter 100 to determine thecurrent state of the environment of the autonomous neighborhoodmulti-copter 152. Other sensors associated with the autonomousneighborhood multi-copter 100 could be operable to provide the speed,heading, altitude, location, and other data such that the computersystem of the autonomous neighborhood multi-copter 100 could determinethe current state of the autonomous neighborhood multi-copter 100.

Based upon the current state of the autonomous neighborhood multi-copter100 and the current state of the environment of the autonomousneighborhood multi-copter 152, the computer system in autonomousneighborhood multi-copter 100 could further determine a predictedbehavior of at least one other entity in the environment of theautonomous neighborhood multi-copter 152. Within the context of FIG. 3A,a set of predicted behaviors 305A (e.g., a predicted behavior, a numberof predicted behaviors) may be determined for both autonomousneighborhood multi-copter 100C and the bird 302A. As the predictedbehaviors 305 could be based on the current state of the environment ofthe autonomous neighborhood multi-copter 152, the computer system of theautonomous neighborhood multi-copter 100 could take into account factorssuch as the speed of the respective autonomous neighborhoodmulti-copters 100, their headings, the weather conditions 119, and otheravailable paths, among other factors. In one embodiment, a change inspeed 306 of the bird 302A may be part of a criteria used to determinepredicted behaviors 305A.

For instance, the autonomous neighborhood aerial vehicle 100C could havea predicted behavior of proceeding at the same speed, and within thesame flight lane. Depending on the embodiment, such a predicted behaviorthat maintains a ‘status quo’ may be considered a default predictedbehavior. Predicted behaviors 305A for the bird 302A could include thebird 302A slowing down to match the speed of the autonomous neighborhoodmulti-copter 100C. Alternatively, the other bird 302A could changeflight lanes to a different flight lane not currently occupied or theother bird 302A could change flight lanes to the flight lane 304A andcut off the autonomous neighborhood multi-copter 100.

Depending upon the embodiment and the situation, a wide variety ofpredicted behaviors 305 of other autonomous neighborhood multi-copters100 could be possible. Possible predicted behaviors 305 could include,but are not limited to, other entities changing flight lanes,accelerating, decelerating, changing heading (e.g., direction and/oraltitude), or entities (e.g., objects, animals, vehicles) exiting theair space. Predicted behaviors 305 could also include other entities(e.g., other autonomous neighborhood multi-copters 100, other vehicles(e.g., cars), bicyclists, pedestrians, animals) pulling over due to anemergency situation, colliding with an obstacle, and colliding withanother entity. Predicted behaviors 305 could be based on what anotherentity may do in response to the autonomous neighborhood multi-copter100 or in response to a third entity (e.g., bird, bicyclist). Otherpredicted behaviors 305 could be determined that relate to any entity(e.g., autonomous neighborhood multi-copter, car, bicycle) behaviorobservable and/or predictable based on the methods and apparatusdisclosed herein.

For each predicted behavior or for a predetermined set of predictedbehaviors 305, the computer system of autonomous neighborhoodmulti-copter 100 could determine corresponding confidence levels. Theconfidence levels could be determined based on the likelihood that thegiven entity (e.g., animal or vehicle) will perform the given predictedbehavior. For instance, if the autonomous neighborhood multi-copter 100Cis highly likely to perform the predicted behavior (staying in thecurrent flight lane, maintaining current speed), the correspondingconfidence level could be determined to be high (e.g., 90%). In someembodiments, the confidence level could be represented as a number, apercentage, or in some other form. With respect to the bird 302A,possible confidence levels could be expressed as follows: slowing downto match speed of autonomous neighborhood multi-copter 100C—40%,maintaining speed and staying in the flight lane 304B 304—40%,maintaining speed and changing to another flight path 300—20%.

The computer system could control autonomous neighborhood multi-copter100 in the autonomous mode based on at least the determined predictedbehaviors 305 and confidence levels. For instance, the computer systemcould take into account the fact the autonomous neighborhoodmulti-copter 100C is highly unlikely to change its rate of speed orflight lane and as such, the computer system could consider autonomousneighborhood multi-copter 100C as a ‘moving obstacle’ that limits thenavigable portion of the path for both the autonomous neighborhoodmulti-copter 100 as well as the bird 302A. The computer system mayfurther consider that there is some finite probability that the bird302A will pull into the flight path 304A and cut off the autonomousneighborhood multi-copter 100. As such, the computer system may causethe autonomous neighborhood multi-copter 100 to slow down slightly, forinstance by reducing the throttle, so as to allow a margin of safety ifthe bird 302A elects to cut in front.

FIG. 3B illustrates a scenario 351 similar to that in FIG. 3A. Inscenario 351, a remote controlled plane 310B has changed its headingtowards the flight lane 304C and has moved closer to the autonomousneighborhood multi-copter 100. The computer system of autonomousneighborhood multi-copter 100 may continuously update the state of theremote controlled plane 310B as well as its environment, for instance ata rate of thirty times per second. Accordingly, the computer system maybe dynamically determining predicted behaviors 305 and theircorresponding confidence levels for remote controlled plane 310B in theenvironment of the autonomous neighborhood multi-copter 152. In scenario351, due at least in part to the changing environment, a new predictedbehavior could be determined for remote controlled plane 310B. In such asituation, the autonomous neighborhood multi-copter 100 may make way forthe remote controlled plane 310B by slowing down. Thus, the predictedbehaviors 305 and corresponding confidence levels 307 could changedynamically.

In scenario 351, the computer system of autonomous neighborhoodmulti-copter 100 could update the confidence level of the predictedbehavior of the other entities (e.g., remote controlled plane 310B). Forinstance, since the remote controlled plane 310B has changed its headingfrom flight lane 304D toward the flight lane 304C and has moved nearerto the autonomous neighborhood multi-copter 100, it may be determinedthat the remote controlled plane 310B is highly likely to change lanesinto the flight lane 304C based on an observed change in angle 308and/or a change in direction 309, according to one embodiment.Accordingly, based on the increased confidence level 307 of thepredicted behavior of the remote controlled plane 310B, the computersystem of the autonomous neighborhood multi-copter 100 could control thedeceleration unit to abruptly slow the autonomous neighborhoodmulti-copter 100 so as to avoid a collision with the remote controlledplane 310B. As such, the computer system of autonomous neighborhoodmulti-copter 100 could carry out a range of different control actions inresponse to varying predicted behaviors 305B (e.g., a set of predicatedbehaviors) and their confidence levels. For example, if another entity(e.g., a plane, another autonomous neighborhood multi-copter, an animal,a pedestrian) is predicted to behave very dangerously and such predictedbehavior has a high confidence level, the computer system of autonomousneighborhood multi-copter 100 could react by aggressively deceleratingor steering the autonomous neighborhood multi-copter 100 evasively toavoid a collision.

Conversely, if the computer system determines that the other entity maycarry out a predicted behavior that is very dangerous, but theconfidence level is very low, the computer system may determine thatonly a minor adjustment in speed is necessary or the computer system maydetermine that no adjustment is required. In one embodiment, theautonomous neighborhood multi-copter 100 may predict a collision betweenremote controlled planes 310A and 310B. The autonomous neighborhoodmulti-copter may be able to adjust its speed and/or course to avoidbeing involved in the collision.

FIG. 3C is a top view of an autonomous neighborhood multi-copter 100operating scenario 352. In scenario 352, an autonomous neighborhoodmulti-copter 100 with a sensor system 102 could be operating in anautonomous mode on land. As such, the sensor system 102 could beobtaining data from the environment of the autonomous neighborhoodmulti-copter 152 and the computer system of the autonomous neighborhoodmulti-copter 100 could be determining a current state of the autonomousneighborhood multi-copter 100 and a current state of the environment ofthe autonomous neighborhood multi-copter 152.

Scenario 352 includes a bicyclist 302A traveling at the same speed andin the same bike lane 307 as the autonomous neighborhood multi-copter100. A bicyclist 302B could be traveling at a higher speed in the sideof the road 300. In such a situation, the computer system of autonomousneighborhood multi-copter 100 could determine predicted behaviors 305A(e.g., a set of predicted behaviors) for the bicyclist 302A andbicyclist 302B. The bicyclist 302B could continue at its current speedand within its current lane. Thus, a ‘default’ predicted behavior couldbe determined. For another possible predicted behavior, the bicyclist302B may also change lanes into the bike lane 307 and cut off theautonomous neighborhood multi-copter 100. The computer system ofautonomous neighborhood multi-copter 100 could determine a defaultpredicted behavior for the bicyclist 302B (e.g., the bicyclist 302B willmaintain present speed and lane).

The computer system of autonomous neighborhood multi-copter 100 coulddetermine confidence levels 307 for each predicted behavior. Forinstance, the confidence level for the bicyclist 302A maintaining speedand the same lane could be relatively high. The confidence level of thebicyclist 302B to change lanes into the bike lane 307 and cut off theautonomous neighborhood multi-copter 100 could be determined to berelatively low, for instance, because the space between the bicyclist302A and the autonomous neighborhood multi-copter 100 is too small tosafely execute a lane change. Further, the confidence level of thebicyclist 302B maintaining its speed and its current lane may bedetermined to be relatively high, at least in part because the side ofthe road 300 is clear ahead. Thus, based on these predictions andconfidence levels, the computer system of autonomous neighborhoodmulti-copter 100 could control the autonomous neighborhood multi-copter100 to maintain its current speed and heading in bike lane 307. In oneembodiment, a change in location 311 could be used to determine aconfidence level for predicted behaviors 305.

FIG. 4 is a scan view 450 of the autonomous neighborhood multi-copter100. Particularly, FIG. 4 shows the sensor system 102 (e.g., the LIDAR108, the RADAR unit 222, the camera 226, a stereo optic sensor, and/oran ultrasound unit 228), a longitudinal axis, an angle β 404, an angle α406, an object 408, and a nature of the object 409. To produce athree-dimensional (3D) image, in one embodiment of the presentinvention, the sensor system 102 may be panned (or oscillated) in, alongand/or out of the longitudinal axis to create a 3D scanning volume 410,as shown in FIG. 4. For sake of illustration, FIG. 4 defines thescanning volume 410 by the angle α 404 (in the vertical scanningdirection) and the angle β 406 (in the horizontal scanning direction).The angle α 404 may range from 30 to 70 degrees, at angular speedsranging from 100-1000 degrees per second. The angle β 406 (i.e., thepanning angle) may range from 1 to 270 degrees, at a panning rateranging from 1-150 degrees per second. Combined the imaging sensorsystem 102 typically can completely scan the 3D scanning volume 410 atmore than two times a second.

In order to accurately determine the distance to objects in the 3Dscanning volume 410, the direction that the sensor system 102 is pointedat the time of receiving light reflected from the objects 408 is needed(i.e., the angle of deflection from the longitudinal axis 402 isneeded). Further, in one embodiment of the present invention, geospatialpositional data of the instantaneous vehicle position is utilized byprocessor (e.g., the processor 202) to calculate based on the distanceof the object from the autonomous neighborhood multi-copter 100 and itsdirection from the autonomous neighborhood multi-copter 100, thegeospatial location of the objects in the field of view. In oneconfiguration of the present invention, the processor may include apersonal computer running on a Linux operating system, and thealgorithms may be programmed in Java programming language. Othercomputing systems and programming languages can be used in the presentinvention. The processor (e.g., the processor 202) may becommunicatively coupled with a real time positioning device, such as forexample the global positioning system (GPS) 218 and/or the internalmeasurement unit 1324, that transmits the location, heading, altitude,and speed of the vehicle multiple times per second to processor. Thereal time positioning device may typically be mounted to the autonomousneighborhood multi-copter 100 and may transmit data (such as location,heading, altitude, and speed of the vehicle) to all imaging sensors(e.g., other LIDAR, radar, ultrasound units 228 and/or cameras) (and allprocessors) on the autonomous neighborhood multi-copter 100.

With commercially available GPS and the INS units, processor objects 102may be able to determine a position of an object in the field of view toan accuracy of better than 10 cm. In one embodiment of the presentinvention, the processor 202 may correlate GPS position, LADARmeasurements, and/or angle of deflection data to produce a map ofobstacles in a path of the autonomous neighborhood multi-copter 100. Theaccuracy of the map may depend on the accuracy of the data from thepositioning device (e.g., the global positioning system 218). Thefollowing are illustrative examples of the accuracies of such data:position 10 cm, forward velocity 0.07 km/hr, acceleration 0.01%,roll/pitch 0.03 degrees, heading 0.1 degrees, lateral velocity 0.2%.

In one embodiment of the present invention, a Kalman filter(commercially integrated) sorts through all data inputs to the processor(e.g., the processor 202). A Kalman filter is a known method ofestimating the state of a system based upon recursive measurement ofnoisy data. In this instance, the Kalman filter is able to much moreaccurately estimate vehicle position by taking into account the type ofnoise inherent in each type of sensor and then constructing an optimalestimate of the actual position. Such filtering is described by A.Kelly, in “A 3d State Space Formulation of a Navigation Kalman Filterfor Autonomous Vehicles,” CMU Robotics Institute, Tech. Rep., 1994, theentire contents of which are incorporated herein by reference. TheKalman filter is a set of mathematical equations that provides anefficient computational (recursive) means to estimate the state of aprocess, in a way that minimizes the mean of the squared error. Thefilter is very powerful in several aspects: it supports estimations ofpast, present, and even future states, and it can do so even when theprecise nature of the modeled system is unknown.

The positioning device, by including GPS and/or INS data, may be able toprovide complementary data to the processor. GPS and INS may havereciprocal errors. That is GPS may be noisy with finite drift, while INSmay not be noisy but may have infinite drift. Further, the processor maybe configured to accept additional inputs (discussed below) to reducedrift in its estimate of vehicle position when, for example the GPS datamay not be available. The nature of the object 409 may include its size,shape, position and/or identity.

FIG. 5A is a multi scan view 550 of the autonomous neighborhoodmulti-copter 100 according to the present invention depicting oneembodiment in which multiple sensors systems 102 (e.g., LIDAR, radar,ultrasound, and/or camera(s)) are used. In this embodiment, one or moreof the imaging sensors (e.g., sensor systems 306) is dedicated toscanning for the detection of objects 408 nearby the autonomousneighborhood multi-copter 100 (e.g., within 50 m) while another of theimaging sensors is dedicated to scanning for the detection of objectsfarther away from the autonomous neighborhood multi-copter 100 (e.g.,beyond 50 m).

In another embodiment of the invention, multiple imaging sensors areused for redundancy and to provide different perspectives of the sameobject. In one embodiment, the autonomous neighborhood multi-copter 100may determine that an alternate field of view is needed. For example,the autonomous neighborhood multi-copter 100 may come to an intersection(while operating on land). However, a car may block the autonomousneighborhood multi-copter's 100 ability to gain a view of theintersection to the right. As the autonomous neighborhood multi-coptermay plan to make a left turn, it must be aware of a traffic flow 5210(shown in FIG. 52) coming from the right. The autonomous neighborhoodmulti-copter 100 may prioritize its established constraints (e.g., theminimum crosswalk stopping distance, the envelope 900, the magnitude ofdeceleration). The autonomous neighborhood multi-copter 100 maydetermine an optimal alternate field of view that does not violateestablished constraints prioritized above obtaining the alternate fieldof view. Achieving this alternate field of view may include moving(rotating, shifting) sensors and/or moving the autonomous neighborhoodmulti-copter 100, according to one environment.

FIG. 5A shows an alternate field of view 502 and an optimal alternatefield of view 504. In an example embodiment, the autonomous neighborhoodmulti-copter 100 may arrive at a stop sign 5206 at an intersection 5200.A car in a next lane may block the view of the autonomous neighborhoodmulti-copter 100. The autonomous neighborhood multi-copter 100 mayrequire the blocked view in order to assess a traffic flow 5210 beforecontinuing along the route. The autonomous neighborhood multi-copter maydetermine that an alternate field of view 502 is required. Theautonomous neighborhood multi-copter may identify a number ofalternative fields of view 502 and/or select the alternate field of viewthat is most efficient at capturing the desired field of view, requiresthe least amount of time and/or effort to attain, and/or does notviolate constraints that have been prioritized above attaining thealternative field of view 502 (e.g., maintaining an envelope 900). Theoptimal alternate field of view may be that which satisfies on or moreof the above mentioned criteria. In the embodiment of FIG. 5A, thealternate field of view 502 and the optimal alternate field of view 504are the same. It should be appreciated that this may not always be thecase.

FIG. 5B is a multi scan view 551 of an autonomous neighborhoodmulti-copter 100 according to the present invention depicting oneembodiment in which multiple imaging sensors systems 102 are used toscan the same or overlapping fields of view. This configuration mayprovide redundant coverage in the center of the path so that, if oneimaging sensor (e.g., the sensor system 102) fails, the other one canstill sense obstacles most likely to be directly in the autonomousneighborhood multi-copter's 100 path. The data from the imaging sensorsmay be correlated by placing all data onto the same elevation grid.

In another embodiment, the imaging sensors may be configured to locateobjects removed from an autonomous neighborhood multi-copter 100; andprocessor (e.g., a sensorprocessor 600 shown in FIG. 6, the processor202 and/or the processor 202) may be configured to direct one of thesensors to scan a first sector associated with a path of the autonomousneighborhood multi-copter 100, while directing another of the sensors toscan a second sector identified with an obstacle (e.g., the object 408).As such, the first and/or second sector determinations can be based on anumber of factors including, but not limited to an autonomousneighborhood multi-copter 100 speed, an identified obstacle location, aprojected path of the autonomous neighborhood multi-copter 100, aresolution required to resolve a complex obstacle or a collection ofobstacles to be resolved, sensory input other than from the sensors, anidentified priority sector in which an obstacle has been identified, andauxiliary information indicating the presence of an obstacle (e.g., theobject 408), a moving obstacle (e.g., a bird, a car, a pedestrian, abike, and/or an animal), another autonomous neighborhood multi-copter100, a landmark, or an area of interest.

In one variant of this embodiment, the processor (e.g., the sensorprocessor 600 shown in FIG. 6, the processor 202 shown in FIG. 2) candirect one sensor to scan (using an angle α 404A, an angle α 404B, anangle β 406A, an/or an angle β 406B as described in FIG. 4) a firstsector associated with a path of the autonomous neighborhoodmulti-copter 100, and in a programmed manner direct the same sensor(e.g., in a dynamic fashion) to scan a second sector identified with anobject 408. Factors which determine the programmed duty cycle by whichone sensor scans the first sector and then a second sector include forexample the speed of the autonomous neighborhood multi-copter 100, theproximity of the obstacle (e.g., the object 408), any movement of theobstacle, an identified status of the obstacle (e.g., friend or foe),the proximity of the obstacle to the projected path of the autonomousneighborhood multi-copter 100, and the calculated clearance from theautonomous neighborhood multi-copter 100 to the obstacle.

Moreover, in one embodiment of the present invention, one of the imagingsensors (e.g., sensor systems 306) is dedicated to scanning in ahorizontal direction while another imaging sensor is directed to scan inthe vertical direction. Scan information from this unit permits theprocessor to better identify the general terrain and terrain curvaturefrom which obstacles can be identified. Complementary data from bothhorizontal and vertical scans helps identity the edges of compositeobstacles (groups of individual obstacles that should be treated as oneobstacle) more accurately. One of the issues with handling movingobstacles is determining the full proportions of an obstacle. Tocalculate the full proportions of an obstacle, multiple “independent”obstacles are intelligently grouped to form one larger compositeobstacle when for example the data points representing the independentobjects 408 (e.g., obstacles) are within a set distance of each other(e.g., within 100 cm). Moreover, in other embodiments of the presentinvention, the grouping into composite obstacles is set by more thanjust a distance of separation between points normally qualifying as anobstacle point. Other factors that can be used in the determinationinclude for example the number of times each point identified as anobstacle is seen, whether the obstacle point moves spatially in time,and whether (as discussed elsewhere) if there is confirmation of theobstacle by other image sensors or stereographic cameras.

Having two completely different perspectives of the obstaclesfacilitates this task by the obstacles being viewed from two separatedimensions (i.e., from top to bottom and from left to right). Since thebeams tend to wrap around the curvature of an obstacle, this providesaccurate estimations of the size and orientation of a compositeobstacle. For instance, consider a spherical boulder. While the backsideof the spherical boulder cannot be seen, the sensing beam maps out acontour of the spherical boulder providing the aforementioned size andorientation, providing an estimate of the full size of the sphericalboulder.

FIG. 6 is an internal sensor system view 650 of the sensor system 102,according to one embodiment. As shown in FIG. 6, the sensor system 102includes a detector 604 for detecting return of an echoed signal. Adetector focusing lens 606 may focus the signal on the detector 604. Thesensor system 102 utilizes a sensor processor 600 for controlling thetiming and emission of the laser pulses 601 and for correlating emissionof the laser pulses 601 with reception of the echoed signal 20. Thesensor processor 600 may be on-board the autonomous neighborhoodmulti-copter 100 or a part of the sensor system 102.

In an exemplary example, laser pulses 601 from emitter 602 pass througha beam expander 614 and a collimator 610. The laser pulses 601 arereflected at a stationary mirror 612 to a rotating mirror 616 and thenforwarded through lens 618 and a telescope 620 to form a beam for thelaser pulses 601 with a diameter of 1-10 mm, providing a correspondingresolution for the synthesized three-dimensional field of view. Thetelescope 620 serves to collect light reflected from objects 22.

In one embodiment of the present invention, the detector 604 isconfigured to detect light only of a wavelength of the emitted light inorder to discriminate the laser light reflected from the object back tothe detector from background light. Accordingly, the sensor system 102operates, in one embodiment of the present invention, by sending out alaser pulse that is reflected by an object 208 and measured by thedetector 604 provided the object is within range of the sensitivity ofthe detector 604. The elapsed time between emission and reception of thelaser pulse permits the sensor processor 600 is used to calculate thedistance between the object 408 and the detector 604. In one embodimentof the present invention, the optics (e.g., the beam expander 614, thecollimator 610, the rotating mirror 616, the stationary mirror 612, thelens 618, and the telescope 620) are configured to direct the beaminstantaneously into a two-dimensional sector of a plane defined withrespect to the longitudinal axis 402, and the detector 604 is afield-programmable gate array for reception of the received signals atpredetermined angular positions corresponding to a respective angulardirection a.

Via the rotating mirror 616, laser pulses 601 are swept through a radialsector a within plane defined with respect to the longitudinal axis 402.In one embodiment of the present invention, in order to accomplishmapping of objects in the field of view in front of the sensor system102, the rotating minor 616 is rotated across an angular displacementranging from 30 to 90 degrees, at angular speeds ranging from 100-10000degrees per second. For example, a 90 degree scanning range can bescanned 75 times per second or an 80 degree scanning range can bescanned between 5 and 100 times per second. Furthermore, the angularresolution can be dynamically adjusted (e.g., providing on commandangular resolutions of 0.01, 0.5, 0.75, or 1 degrees for differentcommercially available sensors (e.g., the sensor system 102, the LIDAR108, the RADAR unit 222, the camera 226, and/or the ultrasound unit228).

Commercially available components can be used for the emitter 602 andthe detector 604 to provide ranging measurements. In one embodiment, theemitter 602, the detector 604, and the associated optics constitute alaser radar (LADAR) system, but other systems capable of making precisedistance measurements can be used in the present invention, such as forexample a light detection and ranging (LIDAR) sensor, a radar, or acamera. LIDAR (Light Detection and Ranging; or Laser Imaging Detectionand Ranging) is a technology that determines distance to an object orsurface using laser pulses Like the similar radar technology, which usesradio waves instead of light, the range to an object is determined bymeasuring the time delay between transmission of a pulse and detectionof the reflected signal. LADAR (Laser Detection and Ranging) refers toelastic backscatter LIDAR systems. The term laser radar is also in use,but with laser radar laser light (and not radio waves) are used.

The primary difference between LIDAR and radar may be that with LIDAR,much shorter wavelengths of the electromagnetic spectrum are used,typically in the ultraviolet, visible, or near infrared. In general itis possible to image a feature or object only about the same size as thewavelength, or larger. Thus, LIDAR may provide more accurate mappingthan radar systems. Moreover, an object may need to produce a dielectricdiscontinuity in order to reflect the transmitted wave. At radar(microwave or radio) frequencies, a metallic object may produce asignificant reflection. However non-metallic objects, such as rain androcks may produce weaker reflections, and some materials may produce nodetectable reflection at all, meaning some objects or features may beeffectively invisible at radar frequencies. Lasers may provide onesolution to these problems. The beam densities and coherency may beexcellent. Moreover the wavelengths may be much smaller than can beachieved with radio systems, and range from about 10 micrometers to theUV (e.g., 250 nm). At these wavelengths, a LIDAR system can offer muchhigher resolution than radar.

FIG. 7 is a detailed schematic illustration of sensor system 102 of thepresent invention. FIG. 7 presents a frontal view of sensor system 102.FIG. 7 shows a motor 702 configured to oscillate the sensor system 102(e.g., the LIDAR 108, the RADAR unit 222, and/or the camera 226) in andout of a plane normal to a predetermined axis (e.g., the longitudinalaxis 402) of the imaging sensor (e.g., the sensor system 102). In oneembodiment of the present invention, a 12-volt DC motor operating at aspeed of 120 RPM is used to oscillate the sensor system 102 in and outthe plane. Other motors with reciprocating speeds different than 120 RPMcan be used.

As shown in FIG. 7, an absolute rotary encoder 704 is placed on a shaft706 that is oscillating. The encoder 704 provides an accurate reading ofthe angle at which the shaft 706 is instantaneously located. By theencoder 704, an accurate measurement of the direction that the sensorsystem 102 is pointed, at the time of the scan, is known. In oneembodiment of the present invention, the encoder 704 is an ethernetoptical encoder (commercially available from Fraba Posital), placed onshaft 706 to provide both the angular position and angular velocity ofthe shaft.

To decrease the delay between reading a value from the sensor andreading a value from the encoder, a separate 100 MBit ethernetconnection with its own dedicated ethernet card connected the sensorprocessor 600 (shown in FIG. 6) with the encoder. This createdcommunications delays between the encoder and the I/O computer that wereconsistent at approximately 0.5 ms. Testing revealed that an actual scan(e.g., LADAR scan) was taken approximately 12.5 ms before the data wasavailable at the I/O computer. When this time was added to the 0.5 ms ofdelay from the encoder communications, a 13 ms delay from the actualscan to the actual reading of the encoder position and velocity waspresent. To counteract the angular offset this delay created, in oneembodiment of the present invention, the velocity of the encoder ismultiplied times the communications delay of 0.013 seconds to calculatethe angular offset due to the delay. This angular offset (which waseither negative or positive depending on the direction of oscillation)was then added to the encoder's position, giving the actual angle at thetime when the scan occurred. This processing permits the orientation ofthe platform (e.g., LADAR platform) to be accurate within 0.05 degrees.

Further, according to the embodiment illustrated in FIG. 7, the metalshaft 706 is attached to a detector bracket 708 which is supported by ametal casing 710 with bearing 712. Bearing 712 is attached to metalcasing 710 with a fastening mechanism such as bolts 714 and 716.Detector bracket 708 is attached to metal shaft 706. Further, as shownin FIG. 7, metal shaft 718 is attached to bearing 720. Bearing 720 isattached to metal casing 710 with a fastening mechanism such as bolts722 and 724. Push rod 726 is attached to detector bracket 708 with balljoint 728 on slot 730. Push rod 726 is attached to pivot spacer 732 withball joint 734. Pivot spacer 732 is attached to servo arm 736 on slot738. Servo arm 736 is attached to metal shaft 740. Motor 702 is attachedto servo arm 736 and is suspended from metal casing 710 by motor mounts742.

The sensor system 102 operates, in one embodiment, by oscillating ameasurement sensor laterally about an axis of the autonomousneighborhood multi-copter 100, as shown in FIG. 4. In the oneembodiment, the shaft 740 of motor 702 rotates at a constant speed,causing servo arm 736 to also spin at a constant speed. One end of Pushrod 726 moves with servo arm 736, causing detector bracket 708 tooscillate back and forth. The degree of rotation can be adjusted bymoving the mount point of ball joint 728 along slot 730, and/or themount point of ball joint 734 along slot 738. Moving the mount pointcloser to shaft 718 increases the angle of rotation, while moving themount point away from shaft 718 decreases the angle of rotation.

While sensor 700 is oscillating, the sensor 700 is taking measurementsof the surrounding environment along the vertical scanning plane, asshown in FIG. 4. The absolute rotary encoder 704 operates as an angularposition mechanism, and transmits the absolute angle of deflection ofdetector bracket 708 to sensor processor 600. At the same time, a realtime positioning device, such as a global positioning system (GPS) 218or an inertial navigation system (INS), transmits the location, heading,altitude, and speed of the vehicle multiple times per second to sensorprocessor 600. Software running on the sensor processor 600 integratesthe data, and, in one embodiment, uses matrix transformations totransform the YZ measurements from each 2D scan (as shown in FIG. 4)into a 3D view of the surrounding environment. Due to the use of thereal time positioning device, in the present invention, a terrain mapcan be calculated even while the vehicle is moving at speeds in excessof 20 miles per hour.

FIG. 8 is a path adjustment view 850 that illustrates results of pathplanning. In FIG. 8, the sensor system 102 of the autonomousneighborhood multi-copter 100 identifies an object 408 in an optimalroute 802. The processor 202 determines that there is adequate clearanceto permit the autonomous neighborhood multi-copter 100 to deviate to theright as it advances to the obstacle 408 and then deviate left to returnto the optimal route 802. The projected path of the autonomousneighborhood multi-copter 100 is shown by different route 804.

In one embodiment, the autonomous neighborhood multi-copter 100 maydetermine that multiple objects 408 block the optimal route 802. Theprocessor 202, working in concert with a sensor fusion algorithm 1338(shown in FIG. 2), may divide the path and a data map into sectors. Thefirst portion of the path may contain no obstacles and require nodeviation along the optimal route 802. The second section may containthe object 408, and a third section may contain an additional obstacle.The object 408 in the second section of the path may require theprocessor 202 to determine clearance and a path around the object 408.Further, deviation from the path may require controlling the speed ofthe autonomous neighborhood multi-copter 100 so as to safely pass theobject 408 (e.g., building) at a speed suited for the radius of theturn. If the object 408 in the third section of the path continues toblock the path of the autonomous neighborhood multi-copter 100, theautonomous neighborhood multi-copter 100 may determine if the autonomousneighborhood multi-copter 100 should remain on the different route 804(e.g., the path taken to avoid the object 408 located in the secondsection), return to the optimal route 802, or take an alternatedifferent route (not show) to avoid the second object 408.

FIG. 9A is an envelope view 950 of the autonomous neighborhoodmulti-copter 100 with an envelope 900 defined by a set of minimum ranges902. A minimum distance 911 in a direction in front 916, behind 918, toa right 914, to a left 913, above, and/or below the autonomousneighborhood multi-copter 100 may compose the envelope 900. In oneembodiment, ultrasound signals (e.g., emitted, relayed and/or processedby an ultrasound unit 228) may be used to monitor and/or maintain theset of minimum ranges 902. In another embodiment, the set of minimumranges 902 may depend on a speed 5307 of the autonomous neighborhoodmulti-copter, a set of weather conditions 119, the environment of theautonomous neighborhood multi-copter 152, the item 4502, and a nature ofthe object 409 that is in close proximity with the autonomousneighborhood multi-copter etc. In FIG. 9A, the set of minimum ranges aredefined in four directions around the vehicle and are useful to definean exemplary envelope 900 around the autonomous neighborhoodmulti-copter 100. Such an envelope 900 can be used to control theautonomous neighborhood multi-copter 100 by monitoring object tracks andchanging neighborhood autonomous vehicle's 100 speed and course to avoidother objects (e.g., the object 408) entering the envelope 900.Additionally, communication with other vehicles (e.g., other autonomousneighborhood multi-copter) can be utilized to coordinate between thevehicles, for example, with both vehicles changing speed and/or courseto avoid either vehicle's envelopes 900 from being entered.

FIG. 9B is an envelope implementation view 951 illustrating the envelope900 of the autonomous neighborhood multi-copter 100 being maintained inpedestrian traffic on the sidewalk 112. In one embodiment, theautonomous neighborhood multi-copter 100 may use a radar signal 908 todetect a range 906A from an object (e.g., the pedestrian 904A). Theautonomous neighborhood multi-copter 100 may adjust speed and/or courseto ensure that the envelope 900 is not breached and avoid collisions.The autonomous neighborhood multi-copter 100 may use ultrasonic rangingsignals 910 (e.g., ultrasound) to detect a range (e.g., a range 906B)from an object (e.g., the pedestrian 904B). In one embodiment, theautonomous neighborhood multi-copter 100 may use its sensors (e.g., theLIDAR 108, the RADAR unit 222, the camera 226, the sensor system 102,and/or the ultrasound unit 228) and/or sensor fusion algorithm 1338 tolocate and/or calculate an optimal route through obstacles (e.g.,pedestrian traffic) in order to maximize travel efficiency (e.g.,minimize travel time) while maintaining the envelope 900.

In another embodiment, the autonomous neighborhood multi-copter 100 maydraft off objects (e.g., bikers, pedestrians), increasing fuel economy.The autonomous neighborhood multi-copter 100 may be able to communicatewith a traffic server in order to gain access to traffic patterns and/ortraffic light patters. The autonomous neighborhood multi-copter 100 maybe able to integrate this information along with pedestrian monitoringtechniques to calculate and/or plan an optimal route and/or reroute toan optimal path (e.g., when the autonomous neighborhood multi-copter 100encounters traffic, delays, construction). Additionally, by integratingpedestrian monitoring techniques with vehicle control methods and byenforcing minimum desirable ranges, the autonomous neighborhoodmulti-copter 100 may be able to maximize efficiency while increasingsafety. Further, the autonomous neighborhood multi-copter 100 may beable to automatically park, deliver items, recharge or refuel (e.g., byautomatically traveling to a fueling area when energy levels reach athreshold level and/or perform necessary steps to charge itself), sendthe itself for maintenance, pick up parcels, perform any other similartasks, and/or return at a set time or on command to a predeterminedlocation.

FIG. 9C is a caravan view 952 of three autonomous neighborhoodmulti-copters 100 in a caravan 912 on the sidewalk 112. In oneembodiment, autonomous neighborhood multi-copters 100 may be caravanned.For example, urbanized areas can use platooned vehicles to implementmass deliveries. A caravan 912 can make circuitous routes in an urbanarea, making scheduled stops or drive-byes to load and/or unload itemsin the caravan 912. Platoons (e.g., caravans 912) may be formed (e.g.,set up to execute large deliveries together) and/or formed on route(e.g., autonomous neighborhood multi-copters 100 may be able to meet upto form a platoon when forming a platoon would improve the capabilitiesof the autonomous neighborhood multi-copters 100 (e.g., allowing them todraft off one another, to expedite deliveries and/or pick-ups, tocoordinate delivery and/or pick up times)). Autonomous neighborhoodmulti-copters 100 may not need to have the same owner, cargo, settings(e.g., envelope settings, speed settings etc.) in order to form thecaravan 912. Caravans 912 may allow the autonomous neighborhoodmulti-copters 100 to travel in closer proximity to one another (e.g.,with smaller sets of minimum rangers 902 of the envelopes 900) thanwould otherwise be permitted.

Minimum ranges for the autonomous neighborhood multi-copter 100 aredesirable in controlling the autonomous neighborhood multi-copter 100,as described in methods above in FIG. 9B. A number of methods to definethe set of minimum ranges 902 are known.

FIG. 10 is a stop time view 1000 that describes one exemplary method toformulate a minimum desirable range in front of the autonomousneighborhood multi-copter 100, in accordance with the presentdisclosure. A minimum stopping time is described to include a timedefined by a minimum time to decelerate, a control reaction time, andadditional factors affecting time to stop.

A minimum time to stop describes a deceleration capacity of theautonomous neighborhood multi-copter 100 at the present speed. Such adeceleration capacity can be determined for a particular autonomousneighborhood multi-copter 100 through many methods, for example, bytesting the autonomous neighborhood multi-copter 100 at various speeds.It will be appreciated that deceleration capacity for differentautonomous neighborhood multi-copter 100 s will be different values, forexample, with a large autonomous neighborhood multi-copter 100 requiringa greater time to stop than a smaller autonomous neighborhoodmulti-copter 100. A control reaction time includes both mechanicalresponses in the autonomous neighborhood multi-copter 100 to an operatoror control module ordering a stop and a response time of the operator orthe control module to an impetus describing a need to stop.

Factors affecting a time to stop include road conditions, weatherconditions, autonomous neighborhood multi-copter 100 maintenanceconditions, including conditions of the deceleration devices on theautonomous neighborhood multi-copter 100 and tire tread (when stoppingthe multi-copter driving on land); operability of autonomousneighborhood multi-copter 100 control systems such as anti-lock brakingand lateral stability control. Factors can include a selectable orautomatically calibrating factor for occupants (e.g., items) in theautonomous neighborhood multi-copter 100. The weight of the multi-copterwith the item may impact the stopping time as well. Time to stop valuescan readily be converted to minimum desirable ranges by one havingordinary skill in the art.

Additionally, the above mentioned method for determining the minimumtime to stop may be used to calculate a magnitude of deceleration. Ifthe calculated magnitude of deceleration is greater than the establishedmaximum magnitude of deceleration, the autonomous neighborhoodmulti-copter 100 may determine if there is an alternative action thatwill not break an established constraint (e.g., the envelope 900 and/oran established maximum speed). The autonomous neighborhood multi-coptermay also prioritize constraints and choose to maintain ones that areprioritized higher than others (e.g., the autonomous neighborhoodmulti-copter 100 may exceed that maximum magnitude of deceleration inorder to avoid a collision when no other viable actions are available).The autonomous neighborhood multi-copter 100 may combine the abovementioned calculations of minimum time to stop (e.g., break when thevehicle is traveling on land) with the predicted behaviors 305 mentionedin FIGS. 3A-C) to decrease speed, alter the path of the autonomousneighborhood multi-copter 100, increase speed etc. For example, if theautonomous neighborhood multi-copter 100 determines that the likelihoodof occurrence of a predicted behavior that would cause the autonomousvehicle to need to decelerate at a magnitude greater than the maximummagnitude of deceleration is above a threshold level, the autonomousneighborhood multi-copter 100 may take proactive measures to avoid sucha scenario (e.g., reduce the speed of the autonomous neighborhoodmulti-copter 100).

FIG. 11 is a GPS monitoring view 1150 depicting an exemplary GPScoordinate monitored through a GPS device combined with 3D map data forthe GPS coordinate. A nominal location 1102 identified through a GPSdevice can be used to describe an area wherein the device can belocated. In FIG. 11, the nominal location 1102 combined with GPS error1106 yields an area wherein the GPS device in the autonomousneighborhood multi-copter 100 can be located or an area of possibleautonomous neighborhood multi-copter 100 locations. In the illustratedembodiment, the nominal location 1102 is located in a flight path 112Hwhile the possible autonomous neighborhood multi-copter location 1104includes areas in a flight lane 112G. The coordinate of the nominallocation 1102 can be coordinated with corresponding coordinates in 3Dmap data, and the area of possible autonomous neighborhood multi-copterlocations 1104 can be projected onto a map.

Within the area of possible autonomous neighborhood multi-copterlocations 1104 made possible by monitoring GPS data, other informationcan be utilized to localize the location of the autonomous neighborhoodmulti-copter 100 within the area of possible autonomous neighborhoodmulti-copter locations 1104 described in FIG. 12. For example, imagerecognition methods can be utilized to identify features on the road infront of the autonomous neighborhood multi-copter 100. In oneembodiment, the sensor fusion algorithm 1338 may combine informationfrom multiple sensors on the autonomous neighborhood multi-copter 100 tomore accurately locate the autonomous neighborhood multi-copter 100.

FIG. 12 is a location identification view 1250 depicting anidentification of a lateral position as well as an angular orientationwith respect to the flight lanes (e.g., a flight lane 304H and a flightlane 304I). This information can be used to place the autonomousneighborhood multi-copter 100 within the area of possible autonomousneighborhood multi-copter 100 locations. Further, lane markers can beexamined, for example, utilizing a dotted line versus a solid line toidentify a lane of travel from possible lanes of travel within thepossible autonomous neighborhood multi-copter 100 locations (when theautonomous neighborhood multi-copter 100 travels on land (e.g., bikelanes and/or roadways)). Additionally, any recognizable featuresidentified within the camera data can be used to fix a location.Recognizable features that can be identified and used in conjunctionwith a 3D map database to determine location include occurrence of anintersection, an off-ramp or on-ramp, encountering a bridge or overpass,approaching an identifiable building, or any other similar detailscontained within the 3D map data.

Methods utilized in FIG. 12 can sufficiently locate the autonomousneighborhood multi-copter 100 or may designate a range of locations oralternate locations where the autonomous neighborhood multi-copter 100might be located.

In one embodiment, a directional signal, such as a radio signal from aknown source or a radar signal return, may be used to localize theposition of an autonomous neighborhood multi-copter 100. In theexemplary determination made in FIG. 12, a range of possible vehiclelocations 1200 has been determined A directional signal from the radiotower depicted allows an intersection between the range of positionswithin the lane determined in FIG. 12 and the direction to the radiotower (not shown) to determine a fixed location of the autonomousneighborhood multi-copter 100. In this way, a combination of informationsources can be utilized to determine a fixed location of an autonomousneighborhood multi-copter 100 with reasonable accuracy.

In an alternate embodiment, a location of an autonomous neighborhoodmulti-copter 100 may be fixed, refining an approximate locationoriginating from a GPS coordinate and a digital map database, first withvisual data or radar data and then with a radio or other wirelessdirectional signal. It will be appreciated that a number of methods tolocalize the position of an autonomous neighborhood multi-copter 100 canbe utilized equally to fix the location of the autonomous neighborhoodmulti-copter 100 to enable the methods described herein. For example, incombination with a GPS signal, visual data, or radar data in combinationwith digital map information, a plurality of radio, radar, or similarsignals originating from known sources can be utilized to localize aposition of an autonomous neighborhood multi-copter 100. In anotherexample, a local communications network could contain a local correctionfactor specific to that geographic location to correct positiondetermined by GPS coordinates. The disclosure is not intended to belimited to the particular examples described herein.

In one embodiment, radar returns or radio returns from two known objectscan be used to triangulate position of an autonomous neighborhoodmulti-copter 100 on a map. Once a position is fixed at some instant intime, another method could determine an estimated change in position ofthe autonomous neighborhood multi-copter 100 by estimating motion of theautonomous neighborhood multi-copter 100, for example, assuming travelalong the present sidewalk 112 based upon a monitored speed, through useof a gyroscopic or accelerometer device, or based upon determining a GPSerror margin by comparing the last fixed location to the GPS nominalposition at that instant and assuming the GPS error margin to be similarfor some period. One having ordinary skill in the art will appreciatethat many such exemplary methods are known, and the disclosure is notintended to be limited to the exemplary methods described herein.

Further, an exemplary infrastructure device includes a GPS differentialdevice, for example, that can be located along roads, communicate withpassing vehicles, and provide a GPS offset value to the autonomousneighborhood multi-copters 100 for a localized area. In such a knowndevice, a GPS nominal location for the device is compared to a fixed,known position for the device, and the difference yields a GPS offsetvalue that can be utilized by vehicles (e.g., the autonomousneighborhood multi-copter 100) operating in the area. Through use ofsuch a device, sensor readings and calculations to triangulate alocation of a host vehicle are unnecessary. Using methods to determine alocation of a leader vehicle in a caravan 912 (e.g., convoy) andcoordinate a number of vehicles based upon the operation of the leadervehicle can be of great advantage to streamlining travel within adensely populated or urban area.

Object tracking is a method whereby a host vehicle utilizes informationsuch as radar returns to determine sequential relative positions of atarget object to the host vehicle. In one embodiment, positions for afirst object (e.g., the autonomous neighborhood multi-copter 100),O.sub.1, and a second object, O.sub.2, are described at sequential timesT.sub.1-T.sub.3. The three plotted positions of object O.sub.1 describean object getting sequentially closer to the host vehicle. Such a trackcan be utilized in a number of ways by the host vehicle (e.g., theautonomous neighborhood multi-copter 100), for example, by comparing arange to O.sub.1 to a minimum allowable range or by determining alikelihood of collision between O.sub.1 and the host vehicle (e.g., theautonomous neighborhood multi-copter 100).

FIG. 12 further depicts exemplary analysis of a vehicle's lateralposition and angle of the autonomous neighborhood multi-copter withrespect to the lane 1202 (theta) based upon sensor information, inaccordance with the present disclosure. The autonomous neighborhoodmulti-copter 100 is depicted including in the sidewalk 112. A visualfield can be described by an area that is represented in a visual image.Boundaries of a visual field that can be analyzed through a visual imagecan be described as an angular area extending outward from the cameracapturing the image. By utilizing image recognition methods, lanemarkers, road features, landmarks, other vehicles on the road, or otherrecognizable images can be utilized to estimate a vehicle position andorientation with respect to sidewalk 112. From analysis of visualimages, a lateral position within lane (e.g., the sidewalk 112), definedby terms A and B defining lateral positioning in the lane, can beestimated, for example, according to distances a and b from the lanemarkers.

Similarly, orientation of the autonomous neighborhood multi-copter 100within the lane can be estimated and described as angle theta. In oneembodiment, the angle of the autonomous neighborhood multi-copter withrespect to the lane 1202 may refer to an angle of the autonomousneighborhood multi-copter with respect to the path (e.g., the plannedpath, the optimal path). This may allow the autonomous neighborhoodmulti-copter 100 to autonomously travel and/or navigate without a needfor lane markers, designated lines, and/or paths. The abovementionedmethods may be used in a three dimensional approach that accounts foraltitude and volume of the flight path.

FIGS. 13A and 13B are exemplary range scans 1350 and 1351 for theautonomous neighborhood multi-copter 100. FIG. 13A depicts a first rangescan 1300 along the road (not shown), in which the segments a-b₁ andc₁-d represent a sidewalk on either side of the road, segments b₁-b₂ andc₁-c₂ represent a curb adjacent to each sidewalk, and the middle segmentb₂-c₂ represents the road. FIG. 13B depicts a second range scan 1302further along the road, in which the segment e-f, in between the segmentb-c, represents an obstacle such as a car on the road in front of theautonomous neighborhood multi-copter 100. In FIGS. 13A and 13B, the beamlines R₀, R_(i), and R_(m), extending from an origin O for each of rangescans 1300 and 1302, represent the distances (ranges) from the laserscanner to the points a, i, and d. The angle α, is the azimuth angle ofthe line O-i with respect to the laser scanner reference.

Due to noise in the range measurements, as well as the configuration andcondition of roads and sidewalks, classification of traversable andnon-traversable areas based on only one range scan is not reliable androbust. Accordingly, the method of the invention builds athree-dimensional road model from cumulated range scans, which aregathered by the laser scanner, and from geo-locations, which areobtained from the navigation unit. This three-dimensional road model,which represents a ground plane, is formulated as a constrainedquadratic surface. The inputted range scan data, after being transformedinto world coordinate points of the three-dimensional road model, canthen be correctly classified based on heights above the ground plane.While the embodiments of FIGS. 13A and 13B relate to land based travel,it will be appreciated by one skilled in the art that the method may beapplied to aerial travel and detection of objects in the air.

FIG. 14 is a user interface view of a group view 1402 associated withparticular geographical location, according to one embodiment.Particularly FIG. 14 illustrates, a map 1400, a groups view 1402,according to one embodiment. In the example embodiment illustrated inFIG. 14, the map view 1400 may display map view of the geographicallocation of the specific group of the global neighborhood environment1800 (e.g., the privacy server 2900 of FIG. 29). The groups view 1402may contain the information (e.g., address, occupant, etc.) associatedwith the particular group of the specific geographical location (e.g.,the geographical location displayed in the map 1400) of the globalneighborhood environment 1800 (e.g., the privacy server 2900 of FIG.29). The members 1404 may contain the information about the membersassociated with the group (e.g., the group associated with geographicallocation displayed in the map) of the global neighborhood environment1800 (e.g., the privacy server 2900 of FIG. 29).

FIG. 15 is a user interface view of claim view 1550, according to oneembodiment. The claim view 1550 may enable the user to claim thegeographical location of the registered user. Also, the claim view 1550may facilitate the user of the global neighborhood environment 1800(e.g., the privacy server 2900 of FIG. 29) to claim the geographicallocation of property under dispute.

In the example embodiment illustrated in FIG. 15, the operation 1502 mayallow the registered user of the global neighborhood environment 1800(e.g., the privacy server 2900 of FIG. 29) to claim the address of thegeographic location claimed by the registered user. The operation 1504illustrated in example embodiment of FIG. 15, may enable the user todelist the claim of the geographical location. The operation 1506 mayoffer information associated with the document to be submitted by theregistered users of the global neighborhood environment 1800 (e.g., theprivacy server 2900 of FIG. 29) to claim the geographical location.

FIG. 16 is a user interface view of a building builder 1602, accordingto one embodiment. Particularly the FIG. 16 illustrates, a map 1600, abuilding builder 1602, according to one embodiment. The map 1600 maydisplay the geographical location in which the verified registered user(e.g., the verified registered user 4110 of FIG. 41A-B) may createand/or modify empty claimable profiles (e.g., the claimable profile 4006of FIG. 40A-41B, the claimable profile 4102 of FIG. 41A, the claimableprofile 1704 of FIG. 17), building layouts, social network pages, andfloor levels structures housing residents and businesses in theneighborhood (e.g., the neighborhood 2902A-N of FIG. 29). The buildingbuilder 1602 may enable the verified registered users (e.g., theverified registered user 4110 of FIG. 41A-B) of the global neighborhoodenvironment 1800 (e.g., the privacy server 2900 of FIG. 29) to drawfloor level structures, add neighbor's profiles and/or may also enableto select the floor number, claimable type, etc. as illustrated inexample embodiment of FIG. 16.

The verified registered user 4110 may be verified registered user of theglobal neighborhood environment 1800 (e.g., the privacy server 2900 ofFIG. 29) interested in creating and/or modifying claimable profiles(e.g., the claimable profile 4006 of FIG. 40A-41B, the claimable profile4102 of FIG. 41A, the claimable profile 1704 of FIG. 17), buildinglayouts, social network pages, and floor level structure housingresidents and businesses in the neighborhood (e.g., the neighborhood2902A-N of FIG. 29) in the building builder 1602.

For example, a social community module (e.g., a social community module2906 of FIG. 29) of the global neighborhood environment 1800 (e.g., theprivacy server 2900 of FIG. 29) may generate a building creator (e.g.,the building builder 1602 of FIG. 16) in which the registered users maycreate and/or modify empty claimable profiles (e.g., the claimableprofile 4006 of FIG. 40A-41B, the claimable profile 4102 of FIG. 41A,the claimable profile 1704 of FIG. 17), building layouts, social networkpages, and floor levels structures housing residents and/or businessesin the neighborhood (e.g., the neighborhood 2902A-N of FIG. 29).

FIG. 17 is a systematic view of communication of claimable data,according to one embodiment. Particularly FIG. 17 illustrates a map1701, verified user profile 1702, choices 1708 and a new claimable page1706, according to one embodiment. The map 1701 may locate the detailsof the address of the registered user of the global neighborhoodenvironment 1800 (e.g., the privacy server 2900 of FIG. 29). Theverified user profile 1702 may store the profiles of the verified userof the global neighborhood environment 1800 (e.g., the privacy server2900 of FIG. 29. The claimable profile 1704 may be the profiles of theregistered user who may claim them in the global neighborhoodenvironment 1800 (e.g., the privacy server 2900 of FIG. 29).

In operation 1700 the search for the user profile (e.g., the userprofile 29200 of FIG. 40A) is been carried whom the registered user maybe searching. The new claimable page 1706 may solicit for the details ofa user whom the registered user is searching for in the globalneighborhood environment 1800 (e.g., the privacy server 2900 of FIG.29). The choices 1708 may ask whether the requested search is any amongthe displayed names. The new claimable page 1706 may request for thedetails of location such as country, state and/or city. The operation1700 may communicate with the choices 1708, and the new claimable page1706.

For example, a no-match module (e.g., a no-match module 3112 of FIG. 31)of the search module (e.g., the search module 2908 of FIG. 29) torequest additional information from the verified registered user about aperson, place, and business having no listing in the global neighborhoodenvironment 1800 (e.g., the privacy server 2900 of FIG. 29) when nomatches are found in a search query of the verified registered user(e.g., the verified registered user 4110 of FIG. 41A-B), and to create anew claimable page 1706 based on a response of the verified registereduser 1702 about the at least one person, place, and business notpreviously indexed in the global neighborhood environment 1800 (e.g.,the privacy server 2900 of FIG. 29).

FIG. 18 is a systematic view of a network view 1850, according to oneembodiment. Particularly it may include a GUI display 1802, a GUIdisplay 1804, device 1806, a device 1808, a network 1810, a router 1812,a switch 1814, a firewall 1816, a load balancer 1818, an applicationserver #3 1820, an application server #2 1822, an application server#11824, a web application server 1826, an inter-process communication1828, a computer server 1830, an image server 1832, a multiple servers1834, a switch 1836, a database storage 1838, database software 1840 anda mail server 1842, according to one embodiment.

The GUI display 1802 and GUI display 1804 may display particular case ofuser interface for interacting with a device capable of representingdata (e.g., computer, cellular telephones, television sets etc.) whichemploys graphical images and widgets in addition to text to representthe information and actions available to the user (e.g., the user 2916of FIG. 29). The device 1806 and device 1808 may be any device capableof presenting data (e.g., computer, cellular telephones, television setsetc.). The network 1810 may be any collection of networks (e.g.,internet, private networks, university social system, private network ofa company etc.) that may transfer any data to the user (e.g., the user2916 of FIG. 29) and the global neighborhood environment 1800 (e.g., theprivacy server 2900 of FIG. 29).

The router 1812 may forward packets between networks and/or informationpackets between the global neighborhood environment 1800 (e.g., theprivacy server 2900 of FIG. 29) and registered user over the network(e.g., internet). The switch 1814 may act as a gatekeeper to and fromthe network (e.g., internet) and the device. The firewall 1816 mayprovides protection (e.g., permit, deny or proxy data connections) fromunauthorized access to the global neighborhood environment 1800 (e.g.,the privacy server 2900 of FIG. 29. The load balancer 1818 may balancethe traffic load across multiple mirrored servers in the globalneighborhood environment 1800 (e.g., the privacy server 2900 of FIG. 29)and may be used to increase the capacity of a server farm beyond that ofa single server and/or may allow the service to continue even in theface of server down time due to server failure and/or servermaintenance.

The application server #2 1822 may be server computer on a computernetwork dedicated to running certain software applications of the globalneighborhood environment 1800 (e.g., the privacy server 2900 of FIG.29). The web application server 1826 may be server holding all the webpages associated with the global neighborhood environment 1800 (e.g.,the privacy server 2900 of FIG. 29). The inter-process communication1828 may be set of rules for organizing and un-organizing factors andresults regarding the global neighborhood environment 1800 (e.g., theprivacy server 2900 of FIG. 29). The computer server 1830 may serve asthe application layer in the multiple servers of the global neighborhoodenvironment 1800 (e.g., the privacy server 2900 of FIG. 29) and/or mayinclude a central processing unit (CPU), a random access memory (RAM)temporary storage of information, and/or a read only memory (ROM) forpermanent storage of information regarding the global neighborhoodenvironment 1800 (e.g., the privacy server 2900 of FIG. 29).

The image server 1832 may store and provide digital images of theregistered user of the global neighborhood environment 1800 (e.g., theprivacy server 2900 of FIG. 29). The multiple servers 1834 may bemultiple computers or devices on a network that may manages networkresources connecting the registered user and the global neighborhoodenvironment 1800 (e.g., the privacy server 2900 of FIG. 29). Thedatabase storage 1838 may store software, descriptive data, digitalimages, system data and any other data item that may be related to theuser (e.g., the user 2916 of FIG. 29) of the global neighborhoodenvironment 1800 (e.g., the privacy server 2900 of FIG. 29). Thedatabase software 1840 may be provided a database management system thatmay support the global neighborhood environment 1800 (e.g., theneighborhood environment 2900 of FIG. 29. The mail server 1842 may beprovided for sending, receiving and storing mails. The device 1806 and1808 may communicate with the GUI display(s) 1802 and 1804, the router1812 through the network 1810 and the global neighborhood environment1800 (e.g., the privacy server 2900 of FIG. 29).

FIG. 19 is a block diagram of a database, according to one embodiment.Particularly the block diagram of the database 1900 of FIG. 19illustrates a user data 1902, a location data, a zip codes data 1906, aprofiles data 1908, a photos data 1910, a testimonials data 1912, asearch parameters data 1914, a neighbor data 1916, a friends requestsdata 1918, a invites data 1920, a bookmarks data 1922, a messages data1924 and a bulletin board data 1926, according to one embodiment.

The database 1900 be may include descriptive data, preference data,relationship data, and/or other data items regarding the registered userof the global neighborhood environment 1800 (e.g., the privacy server2900 of FIG. 29.

The user data 1902 may be a descriptive data referring to informationthat may describe a user (e.g., the user 2916 of FIG. 29). It mayinclude elements in a certain format for example Id may be formatted asinteger, Firstname may be in text, Lastname may be in text, Email may bein text, Verify may be in integer, Password may be in text, Gender maybe in m/f, Orientation may be in integer, Relationship may be in y/n,Dating may be in y/n, Friends may be in y/n, Activity may be in y/n,Status may be in integer, Dob may be in date, Country may be in text,Zip code may be in text, Postalcode may be in text, State may be intext, Province may be in text, City may be in text, Occupation may be intext, Location may be in text, Hometown may be in text, Photo may be ininteger, Membersince may be in date, Lastlogin may be in date,Lastupdate may be in date, Recruiter may be in integer, Friendcount maybe in integer, Testimonials may be in integer, Weeklypdates may be iny/n, Notifications may be in y/n, Photomode may be in integer and/orType may be in integer.

The locations data 1904 may clarify the location details in formattedapproach. For example Zip code may be formatted as integer, City may bein text and/or State may be in text. The zip codes data 1906 may provideinformation of a user location in formatted manner. For example Zip codemay be formatted as text, Latitude may be in integer and/or Longitudemay be in integer. The profile data 1908 may clutch personneldescriptive data that may be formatted.

For examples ID may be formatted as integer, Interests may be in text,Favoritemusic may be in text, Favaoritebooks may be in text, Favoritetvmay be in text, Favoritemovies may be in text, Aboutme may be in text,Wanttommet may be in text, Ethnicity may be in integer, Hair may be ininteger, Eyes may be in integer, Height may be in integer, Body may bein integer, Education may be in integer, Income may be in integer,Religion may be in integer, Politics may be in integer Smoking may be ininteger, Drinking may be in integer and/or Kids may be in integer.

The photos data 1910 may represent a digital image and/or a photographof the user formatted in certain approach. For example Id may beformatted as integer, User may be in integer, Fileid may be in integerand/or Moderation may be in integer. The testimonials data 1912 mayallow users to write “testimonials” 1912, or comments, about each otherand in these testimonials, users may describe their relationship to anindividual and their comments about that individual. For example theuser might write a testimonial that states “Rohan has been a friend ofmine since graduation days. He is smart, intelligent, and a talentedperson.” The elements of testimonials data 1912 may be formatted as Idmay be in integer, User may be in integer, Sender may be integer,Approved may be in y/n, Date may be in date and/or Body may be formattedin text.

The search parameters data 1914 may be preference data referring to thedata that may describe preferences one user has with respect to another(For example, the user may indicate that he is looking for a female whois seeking a male for a serious relationship). The elements of thesearch parameters data 1914 may be formatted as User 1902 may be ininteger, Photosonly may be in y/n, Justphotos may be in y/n, Male may bein y/n, Female may be in y/n, Men may be in y/n, Women may be in y/n,Helptohelp may be in y/n, Friends may be in y/n, Dating may be in y/n,Serious may be in y/n, Activity may be in y/n, Minage may be in integer,Maxage may be in integer, Distance may be in integer, Single may be iny/n, Relationship may be in y/n, Married may be in y/n and/orOpenmarriage may be in y/n.

The neighbor's data 1916 may generally refer to relationships amongregistered users of the global neighborhood environment 1800 (e.g., theprivacy server 2900 of FIG. 29) that have been verified and the user hasrequested another individual to join the system as neighbor 1916, andthe request may be accepted. The elements of the neighbors data 1916 maybe formatted as user1 may be in integer and/or user2 may be in integer.The friend requests data 1918 may tracks requests by users within theneighborhood (e.g., the neighborhood 2902A-N of FIG. 29) to otherindividuals, which requests have not yet been accepted and may containelements originator and/or respondent formatted in integer. The invitesdata 1920 may describe the status of a request by the user to invite anindividual outside the neighborhood (e.g., the neighborhood 2902A-N ofFIG. 29) to join the neighborhood (e.g., the neighborhood 2902A-N ofFIG. 29) and clarify either the request has been accepted, ignoredand/or pending.

The elements of the invites data 1920 may be formatted as Id may be ininteger, Key may be in integer, Sender may be in integer, Email may bein text, Date may be in date format, Clicked may be in y/n, Joined maybe in y/n and/or Joineduser may be in integer. The bookmarks data 1922may be provide the data for a process allowed wherein a registered userof the global neighborhood environment 1800 (e.g., the privacy server2900 of FIG. 29) may indicate an interest in the profile of anotherregistered user. The bookmark data 1922 elements may be formatted asOwner may be in integer, User may be in integer and/or Visible may be iny/n. The message data 1924 may allow the users to send one anotherprivate messages.

The message data 1924 may be formatted as Id may be in integer, User maybe in integer, Sender may be in integer, New may be in y/n, Folder maybe in text, Date may be in date format, Subject may be in text and/orBody may be in text format. The bulletin board data 1926 may supportsthe function of a bulletin board that users may use to conduct onlinediscussions, conversation and/or debate. The claimable data 1928 mayshare the user profiles (e.g., the user profile 29200 of FIG. 40A) inthe neighborhood (e.g., the neighborhood 2902A-N of FIG. 29) and itselements may be formatted as claimablesinputed and/or others may be intext format.

FIG. 20 is an exemplary graphical user interface view for datacollection, according to one embodiment. Particularly FIG. 20illustrates exemplary screens 2002, 2004 that may be provided to theuser (e.g., the user 2916 of FIG. 29) through a user interface 1802 maybe through the network (e.g., Internet), to obtain user descriptivedata. The screen 2002 may collect data allowing the user (e.g., the user2916 of FIG. 29) to login securely and be identified by the neighborhood(e.g., the neighborhood 2902A-N of FIG. 29). This screen 2002 may allowthe user to identify the reason he/she is joining the neighborhood. Forexample, a user may be joining the neighborhood for “neighborhoodwatch”. The screen 2004 may show example of how further groups may bejoined. For example, the user (e.g., the user 2916 of FIG. 29) may bewilling to join a group “Raj for city council”. It may also enclose thedata concerning Dob, country, zip/postal code, hometown, occupationand/or interest.

FIG. 21 is an exemplary graphical user interface view of imagecollection, according to one embodiment. A screen 2100 may be interfaceprovided to the user (e.g., the user 2916 of FIG. 29) over the network(e.g., internet) may be to obtain digital images from system user. Theinterface 2102 may allow the user (e.g., the user 2916 of FIG. 29) tobrowse files on his/her computer, select them, and then upload them tothe neighborhood (e.g., the neighborhood 2902A-N of FIG. 29). The user(e.g., the user 2916 of FIG. 29) may upload the digital images and/orphoto that may be visible to people in the neighbor (e.g., the neighbor2920 of FIG. 29) network and not the general public. The user may beable to upload a JPG, GIF, PNG and/or BMP file in the screen 2100.

FIG. 22 is an exemplary graphical user interface view of an invitation,according to one embodiment. An exemplary screen 2200 may be provided toa user through a user interface 2202 may be over the network (e.g.,internet) to allow users to invite neighbor or acquaintances to join theneighborhood (e.g., the neighborhood 2902A-N of FIG. 29). The userinterface 2202 may allow the user (e.g., the user 2916 of FIG. 29) toenter one or a plurality of e-mail addresses for friends they may liketo invite to the neighborhood (e.g., the neighborhood 2902A-N of FIG.29). The exemplary screen 2200 may include the “subject”, “From”, “To”,“Optional personnel message”, and/or “Message body” sections. In the“Subject” section a standard language text may be included for joiningthe neighborhood (e.g., Invitation to join Fatdoor from John Doe, aneighborhood.).

The “From” section may include the senders email id (e.g.,user@domain.com). The “To” section may be provided to add the email idof the person to whom the sender may want to join the neighborhood(e.g., the neighborhood 2902A-N of FIG. 29). The message that may besent to the friends and/or acquaintances may include standard languagedescribing the present neighborhood, the benefits of joining and thesteps required to join the neighborhood (e.g., the neighborhood 2902A-Nof FIG. 29). The user (e.g., the user 2916 of FIG. 29) may choose toinclude a personal message, along with the standard invitation in the“Optional personal message” section. In the “Message body” section theinvited friend or acquaintance may initiate the process to join thesystem by clicking directly on an HTML link included in the e-mailmessage (e.g., http://www.fatdoor.com/join.jsp? Invite=140807). In oneembodiment, the user (e.g., the user 2916 of FIG. 29) may import e-mailaddresses from a standard computerized address book. The system mayfurther notify the inviting user when her invitee accepts or declinesthe invitation to join the neighborhood (e.g., the neighborhood 2902A-Nof FIG. 29).

FIG. 23 is a flowchart of inviting the invitee(s) by the registereduser, notifying the registered user upon the acceptance of theinvitation by the invitee(s) and, processing and storing the input dataassociated with the user (e.g., the user 2916 of FIG. 29) in thedatabase, according to one embodiment. In operation 2302, the verifiedregistered user (e.g., the verified registered user 4110 of FIG. 41A-B,the verified registered user 4110 of FIG. 16) willing to invite theindividual enters the email addresses of an individual “invitee”. Inoperation 2304, the email address and the related data of the inviteemay be stored in the database. In operation 2306, the invitation contentfor inviting the invitee may be generated from the data stored in thedatabase. In operation 2308, the registered user sends invitation to theinvitee(s).

In operation 2310, response from the user (e.g., the user 2916 of FIG.29) may be determined. The operation 2312, if the invitee doesn'trespond to invitation sent by the registered user then registered usermay resend the invitation for a predefined number of times. In operation2314, if the registered user resends the invitation to the same inviteefor predefined number of times and if the invitee still doesn't respondto the invitation the process may be terminated automatically.

In operation 2316, if the invitee accepts the invitation sent by theregistered user then system may notify the registered user that theinvitee has accepted the invitation. In operation 2318, the input fromthe present invitee(s) that may contain the descriptive data about thefriend (e.g., registered user) may be processed and stored in thedatabase.

For example, each registered user associated e-mail addresses ofindividuals who are not registered users may be stored and identified byeach registered user as neighbors. An invitation to become a new user(e.g., the user 2916 of FIG. 29) may be communicated out to neighbor(e.g., the neighbors neighbor of FIG. 29) of the particular user. Anacceptance of the neighbor (e.g., the neighbor 2920 of FIG. 29) to whomthe invitation was sent may be processed.

The neighbor (e.g., the neighbor 2920 of FIG. 29) may be added to adatabase and/or storing of the neighbor (e.g., the neighbor 2920 of FIG.29), a user ID and a set of user IDs of registered users who aredirectly connected to the neighbor (e.g., the neighbor 2920 of FIG. 29),the set of user IDs stored of the neighbor (e.g., the neighbor 2920 ofFIG. 29) including at least the user ID of the verified registered user(e.g., the verified registered user 4110 of FIG. 41A-B, the verifiedregistered user 4110 of FIG. 16). Furthermore, the verified registereduser may be notified that the invitation to the neighbor (e.g., theneighbor 2920 of FIG. 29) has been accepted when an acceptance isprocessed. Also, inputs from the neighbor (e.g., the neighbor 2920 ofFIG. 29) having descriptive data about the friend may be processed andthe inputs in the database may be stored.

FIG. 24 is a flowchart of adding the neighbor (e.g., the neighbor 2920of FIG. 29) to the queue, according to one embodiment. In operation2402, the system may start with the empty connection list and emptyqueue. In operation 2404, the user may be added to the queue. Inoperation 2406, it is determined whether the queue is empty. Inoperation 2408, if it is determined that the queue is not empty then thenext person P may be taken from the queue. In operation 2410, it may bedetermined whether the person P from the queue is user B or not. Inoperation 2412, if the person P is not user B then it may be determinedwhether the depth of the geographical location is less than maximumdegrees of separation.

If it is determined that depth is more than maximum allowable degrees ofseparation then it may repeat the operation 2408. In operation 2414, ifmay be determined that the depth of the geographical location (e.g., thegeographical location 4004 of FIG. 40A) is less than maximum degrees ofseparation then the neighbors (e.g., the neighbor 2920 of FIG. 29) listfor person P may be processed. In operation 2416, it may be determinedwhether all the neighbors (e.g., the neighbor 2920 of FIG. 29) in theneighborhood (e.g., the neighborhood 2902A-N of FIG. 29) have beenprocessed or not. If all the friends are processed it may be determinedthe queue is empty.

In operation 2418, if all the neighbors (e.g., the neighbor 2920 of FIG.29) for person P are not processed then next neighbor N may be takenfrom the list. In operation 2420, it may be determined whether theneighbor (e.g., the neighbor 2920 of FIG. 29) N has encountered beforeor not. In operation 2422, if the neighbor (e.g., the neighbor 2920 ofFIG. 29) has not been encountered before then the neighbor may be addedto the queue. In operation 2424, if the neighbor N has been encounteredbefore it may be further determined whether the geographical location(e.g., the geographical location 4004 of FIG. 40A) from where theneighbor (e.g., the neighbor 2920 of FIG. 29) has encountered previouslyis the same place or closer to that place.

If it is determined that the neighbor (e.g., the neighbor 2920 of FIG.29) has encountered at the same or closer place then the friend may beadded to the queue. If it may be determined that friend is notencountered at the same place or closer to that place then it may beagain checked that all the friends have processed. In operation 2426, ifit is determined that the person P is user B than the connection may beadded to the connection list and after adding the connection toconnection list it follows the operation 2412. In operation 2428, if itmay be determined that queue is empty then the operation may return theconnections list.

For example, a first user ID with the verified registered user (e.g.,the verified registered user 4110 of FIG. 41A-B, the verified registereduser 4110 of FIG. 16) and a second user ID may be applied to thedifferent registered user. The verified registered user (e.g., theverified registered user 4110 of FIG. 41A-B, the verified registereduser 4110 of FIG. 16) with the different registered user may beconnected with each other through at least one of a geo-positioning dataassociated with the first user ID and the second user ID. In addition, amaximum degree of separation (Nmax) of at least two that is allowed forconnecting any two registered users, (e.g., the two registered users whomay be directly connected may be deemed to be separated by one degree ofseparation and two registered users who may be connected through no lessthan one other registered user may be deemed to be separated by twodegrees of separation and two registered users who may be connectedthrough not less than N other registered users may be deemed to beseparated by N+1 degrees of separation).

Furthermore, the user ID of the different registered user may besearched (e.g., the method limits the searching of the differentregistered user in the sets of user IDs that may be stored as registeredusers who are less than Nmax degrees of separation away from theverified registered user (e.g., the verified registered user 4110 ofFIG. 41A-B, the verified registered user 4110 of FIG. 16), such that theverified registered user (e.g., the verified registered user 4110 ofFIG. 41A-B, the verified registered user 4110 of FIG. 16) and thedifferent registered user who may be separated by more than Nmax degreesof separation are not found and connected.) in a set of user IDs thatmay be stored of registered users who are less than Nmax degrees ofseparation away from the verified registered user (e.g., the verifiedregistered user 4110 of FIG. 41A-B, the verified registered user 4110 ofFIG. 16), and not in the sets of user IDs that may be stored forregistered users who are greater than or equal to Nmax degrees ofseparation away from the verified registered user (e.g., the verifiedregistered user 4110 of FIG. 41A-B, the verified registered user 4110 ofFIG. 16), until the user ID of the different registered user may befound in one of the searched sets. Also, the verified registered user(e.g., the verified registered user 4110 of FIG. 41A-B, the verifiedregistered user 4110 of FIG. 16) may be connected to the differentregistered user if the user ID of the different registered user may befound in one of the searched sets.

Moreover, the sets of user IDs that may be stored of registered usersmay be searched initially who are directly connected to the verifiedregistered user (e.g., the verified registered user 4110 of FIG. 41A-B,the verified registered user 4110 of FIG. 16). A profile of thedifferent registered user may be communicated to the verified registereduser (e.g., the verified registered user 4110 of FIG. 41A-B, theverified registered user 4110 of FIG. 16) to display through a markerassociating the verified registered user (e.g., the verified registereduser 4110 of FIG. 41A-B, the verified registered user 4110 of FIG. 16)with the different registered user. A connection path between theverified registered user (e.g., the verified registered user 4110 ofFIG. 41A-B, the verified registered user 4110 of FIG. 16) and thedifferent registered user, the connection path indicating at least oneother registered user may be stored through whom the connection pathbetween the verified registered user (e.g., the verified registered user4110 of FIG. 41A-B, the verified registered user 4110 of FIG. 16) andthe different registered user is made.

In addition, the connection path between the verified registered user(e.g., the verified registered user 4110 of FIG. 41A-B, the verifiedregistered user 4110 of FIG. 16) and the different registered user maybe communicated to the verified registered user to display. A hyperlinkin the connection path of each of the at least one registered users maybe embedded through whom the connection path between the verifiedregistered user (e.g., the verified registered user 4110 of FIG. 41A-B,the verified registered user 4110 of FIG. 16) and the differentregistered user is made.

FIG. 25 is a flowchart of communicating brief profiles of the registeredusers, processing a hyperlink selection from the verified registereduser (e.g., the verified registered user 4110 of FIG. 41A-B, theverified registered user 4110 of FIG. 16) and calculating and ensuringthe Nmax degree of separation of the registered users away from verifiedregistered users (e.g., the verified registered user 4110 of FIG. 41A-B,the verified registered user 4110 of FIG. 16), according to oneembodiment. In operation 2502, the data of the registered users may becollected from the database. In operation 2504, the relational pathbetween the first user and the second user may be calculated (e.g., theNmax degree of separation between verified registered user (e.g., theverified registered user 4110 of FIG. 41A-B, the verified registereduser 4110 of FIG. 16) and the registered user).

For example, the brief profiles of registered users, including a briefprofile of the different registered user, to the verified registereduser (e.g., the verified registered user 4110 of FIG. 41A-B, theverified registered user 4110 of FIG. 16) for display, each of the briefprofiles including a hyperlink to a corresponding full profile may becommunicated.

Furthermore, the hyperlink selection from the verified registered user(e.g., the verified registered user 4110 of FIG. 41A-B, the verifiedregistered user 4110 of FIG. 16) may be processed (e.g., upon processingthe hyperlink selection of the full profile of the different registereduser, the full profile of the different registered user may becommunicated to the verified registered user (e.g., the verifiedregistered user 4110 of FIG. 41A-B, the verified registered user 4110 ofFIG. 16) for display). In addition, the brief profiles of thoseregistered users may be ensured who are more than Nmax degrees ofseparation away from the verified registered user (e.g., the verifiedregistered user 4110 of FIG. 41A-B, the verified registered user 4110 ofFIG. 16) are not communicated to the verified registered user (e.g., theverified registered user 4110 of FIG. 41A-B, the verified registereduser 4110 of FIG. 16) for display.

FIG. 26 is an N degree separation view 2650, according to oneembodiment. ME may be a verified registered user (e.g., the verifiedregistered user 4110 of FIG. 41A-B, the verified registered user 4110 ofFIG. 16) of the global neighborhood environment 1800 (e.g., the privacyserver 2900 of FIG. 29) centered in the neighborhood network. A, B, C,D, E, F, G, H, I, J, K, L, M, N, O, P, Q, R, S, T, and/or U may be theother registered user of the neighborhood network. The member of theneighborhood network may be separated from the centered verifiedregistered user (e.g., the verified registered user 4110 of FIG. 41A-B,the verified registered user 4110 of FIG. 16) ME of the neighborhoodnetwork by certain degree of separation. The registered user A, B and Cmay be directly connected and are deemed to be separated by one degreeof separation from verified registered user (e.g., the verifiedregistered user 4110 of FIG. 41A-B, the verified registered user 4110 ofFIG. 16) ME. The registered user D, E, F, G, and H may be connectedthrough no less than one other registered user may be deemed to beseparated by two degree of separation from verified registered user(e.g., the verified registered user 4110 of FIG. 41A-B, the verifiedregistered user 4110 of FIG. 16) ME. The registered user I, J, K, and Lmay be connected through no less than N−1 other registered user may bedeemed to be separated by N degree of separation from verifiedregistered user (e.g., the verified registered user 4110 of FIG. 41A-B,the verified registered user 4110 of FIG. 16) ME. The registered user M,N, O, P, Q, R S, T and U may be all registered user.

FIG. 27 is a user interface view 2700 showing a map, according to oneembodiment. Particularly FIG. 27 illustrates a satellite photo of aphysical world. The registered user of the global neighborhoodenvironment 1800 (e.g., the privacy server 2900 of FIG. 29) may use thisfor exploring the geographical location (e.g., the geographical location4004 of FIG. 40A) of the neighbors (e.g., the neighbor 2920 of FIG. 29).The registered user (e.g., the verified registered user 4110 of FIG.41A-B, the verified registered user 4110 of FIG. 16) may navigate, zoom,explore and quickly find particular desired geographical locations ofthe desired neighbors (e.g., the neighbor 2920 of FIG. 29). This mayhelp the registered user to read the map and/or plot the route of theneighbors (e.g., the neighbor 2920 of FIG. 29) on the world map.

FIG. 28A is a process flow of searching map based community andneighborhood contribution, according to one embodiment. In operation2802, a verified registered user (e.g., a verified registered user 4110of FIG. 41A-13B, a verified registered user 4110 of FIG. 16) may beassociated with a user profile (e.g., a user profile 29200 of FIG. 40A).In operation 2804, the user profile (e.g., the user profile 29200 ofFIG. 40A) may be associated with a specific geographic location (e.g., ageographic location 4004 of FIG. 40A).

In operation 2806, a map (e.g., a map 4002 of FIG. 40A-41B, a map 1400of FIG. 14, a map 1600 of FIG. 16, a map 1701 of FIG. 17) may begenerated concurrently displaying the user profile (e.g., the userprofile 29200 of FIG. 40A) and the specific geographic location (e.g.,the geographic location 4004 of FIG. 40A). In operation, 2808, in themap, claimable profiles (e.g., a claimable profile 4006 of FIG. 40A-B, aclaimable profile 4102 of FIG. 41A, a claimable profile 1704 of FIG. 17)associated with different geographic locations may be simultaneouslygenerated surrounding the specific geographic location (e.g., thegeographic location 4004 of FIG. 40A) associated with the user profile(e.g., the user profile 29200 of FIG. 40A).

In operation 2810, a query of at least one of the user profile (e.g.,the user profile 29200 of FIG. 40A) and the specific geographic location(e.g., the geographic location 4004 of FIG. 40A) may be processed. Inoperation 2812, a particular claimable profile of the claimable profiles(e.g., the claimable profile 4006 of FIG. 40A-B, the claimable profile4102 of FIG. 41A, the claimable profile 1704 of FIG. 17) may beconverted to another user profile (e.g., the user profile 29200 of FIG.40A) when a different registered user claims a particular geographiclocation to the specific geographic location (e.g., the geographiclocation 4004 of FIG. 40A) associated with the particular claimableprofile (e.g., the claimable profile 4006 of FIG. 40A-B, the claimableprofile 4102 of FIG. 41A, the claimable profile 1704 of FIG. 17),wherein the user profile (e.g., the user profile 29200 of FIG. 40A) maybe tied to a specific property in a neighborhood (e.g., a neighborhood2902A-2902N of FIG. 29), and wherein the particular claimable profile(e.g., the claimable profile 4006 of FIG. 40A-41B, the claimable profile4102 of FIG. 41A, the claimable profile 1704 of FIG. 17) may beassociated with a neighboring property to the specific property in theneighborhood (e.g., the neighborhood 2920A-2920N of FIG. 29).

In operation 2814, a certain claimable profile (e.g., the claimableprofile 4006 of FIG. 40A-41B, the claimable profile 4102 of FIG. 41A,the claimable profile 1704 of FIG. 17) of the claimable profiles (e.g.,the claimable profile 4006 of FIG. 40A-B, the claimable profile 4102 ofFIG. 41A, the claimable profile 1704 of FIG. 17) may be delisted when aprivate registered user claims a certain geographic location (e.g., thegeographic location 4004 of FIG. 40A) adjacent to at least one of thespecific geographic location and the particular geographic location(e.g., the geographic location 4004 of FIG. 40A).

In operation 2816, the certain claimable profile (e.g., the claimableprofile 4006 of FIG. 40A-B, the claimable profile 4102 of FIG. 41A, theclaimable profile 1704 of FIG. 17) in the map (e.g., the map 4002 ofFIG. 40A-B, the map 1400 of FIG. 14, the map 1600 of FIG. 16, the map1701 of FIG. 17) when the certain claimable profile may be delistedand/or be masked through the request of the private registered user.

FIG. 28B is a continuation of process flow of FIG. 28A showingadditional processes, according to one embodiment. In operation 2818, atag data associated with at least one of the specific geographiclocation, the particular geographic location (e.g., the geographiclocation 4004 of FIG. 40A), and the delisted geographic location may beprocessed. In operation 2820, a frequent one of the tag data may bedisplayed when at least one of the specific geographic location and theparticular geographic location (e.g., the geographic location 4004 ofFIG. 40A) may be made active, but not when the geographic location(e.g., the geographic location 4004 of FIG. 40A) may be delisted.

In operation 2822, a commercial user (e.g., a commercial user 4100 ofFIG. 41A-B) may be permitted to purchase a customizable business profile(e.g., a customizable business profile 4104 of FIG. 41B) associated witha commercial geographic location. In operation 2824, the verifiedregistered user (e.g., the verified registered user 4110 of FIG. 41A-B,the verified registered user 4110 of FIG. 16) to communicate a messageto the neighborhood (e.g., the neighborhood 2902A-2902N of FIG. 29) maybe enabled based on a selectable distance range away from the specificgeographic location.

In operation 2826, a payment of the commercial user (e.g., thecommercial user 4100 of FIG. 41A-B) and the verified registered user(e.g., the verified registered user 4110 of FIG. 41A-B, the verifiedregistered user 4110 of FIG. 16) may be processed. In operation 2828,the verified registered user (e.g., the verified registered user 4110 ofFIG. 41A-B, the verified registered user 4110 of FIG. 16) may bepermitted to edit any information in the claimable profiles (e.g., theclaimable profile 4006 of FIG. 40A-B, the claimable profile 4102 of FIG.41A, the claimable profile 1704 of FIG. 17) including the particularclaimable profile and the certain claimable profile until the certainclaimable profile may be claimed by at least one of the differentregistered user and the private registered user.

In operation 2830, a claimant of any claimable profile (e.g., theclaimable profile 4006 of FIG. 40A-B, the claimable profile 4102 of FIG.41A, the claimable profile 1704 of FIG. 17) may be enabled to controlwhat information is displayed on their user profile (e.g., the userprofile 29200 of FIG. 40A). In operation 2832, the claimant to segregatecertain information on their user profile (e.g., the user profile 29200of FIG. 40A) may be allowed such that only other registered usersdirectly connected to the claimant are able to view data on their userprofile (e.g., the user profile 29200 of FIG. 40A).

FIG. 28C is a continuation of process flow of FIG. 28B showingadditional processes, according to one embodiment. In operation 2834, afirst user ID with the verified registered user (e.g., the verifiedregistered user 4110 of FIG. 41A-B, the verified registered user 4110 ofFIG. 16) and a second user ID to the different registered user may beapplied. In operation 2836, the verified registered user (e.g., theverified registered user 4110 of FIG. 41A-B, the verified registereduser 4110 of FIG. 16) with the different registered user with each othermay be connected through at least one of associated with the first userID and the second user ID.

In operation 2838, a maximum degree of separation (Nmax) of at least twomay be set that is allowed for connecting any two registered users,wherein two registered users who are directly connected may be deemed tobe separated by one degree of separation and two registered users whoare connected through no less than one other registered user may bedeemed to be separated by two degrees of separation and two registeredusers who may be connected through no less than N other registered usersare deemed to be separated by N+1 degrees of separation. In operation2840, the user ID of the different registered user may be searched in aset of user IDs that are stored of registered users who are less thanNmax degrees of separation away from the verified registered user (e.g.,the verified registered user 4110 of FIG. 41A-B, the verified registereduser 4110 of FIG. 16), and not in the sets of user IDs that are storedfor registered users who may be greater than or equal to Nmax degrees ofseparation away from the verified registered user (e.g., the verifiedregistered user 4110 of FIG. 41A-B, the verified registered user 4110 ofFIG. 16), until the user ID of the different registered user may befound in one of the searched sets.

In operation 2842, the verified registered user (e.g., the verifiedregistered user 4110 of FIG. 41A-B, the verified registered user 4110 ofFIG. 16) may be connected to the different registered user if the userID of the different registered user may be found in one of the searchedsets, wherein the method limits the searching of the differentregistered user in the sets of user IDs that may be stored of registeredusers who may be less than Nmax degrees of separation away from theverified registered user (e.g., the verified registered user 4110 ofFIG. 41A-B, the verified registered user 4110 of FIG. 16), such that theverified registered user (e.g., the verified registered user 4110 ofFIG. 41A-B, the verified registered user 4110 of FIG. 16) and thedifferent registered user who may be separated by more than Nmax degreesof separation are not found and connected. In operation 2844, initiallyin the sets of user IDs that are stored of registered users who may bedirectly connected to the verified registered user (e.g., the verifiedregistered user 4110 of FIG. 41A-B, the verified registered user 4110 ofFIG. 16) may be initially searched.

FIG. 28D is a continuation of process flow of FIG. 28C showingadditional processes, according to one embodiment. In operation 2846, aprofile of the different registered user to the verified registered user(e.g., the verified registered user 4110 of FIG. 41A-B, the verifiedregistered user 4110 of FIG. 16) to display may be communicated througha marker associating the verified registered user (e.g., the verifiedregistered user 4110 of FIG. 41A-B, the verified registered user 4110 ofFIG. 16) with the different registered user.

In operation 2848, a connection path between the verified registereduser (e.g., the verified registered user 4110 of FIG. 41A-B, theverified registered user 4110 of FIG. 16) and the different registereduser, the connection path indicating at least one other registered usermay be stored through whom the connection path between the verifiedregistered user (e.g., the verified registered user 4110 of FIG. 41A-B,the verified registered user 4110 of FIG. 16) and the differentregistered user may be made.

In operation 2850, the connection path between the verified registereduser (e.g., the verified registered user 4110 of FIG. 41A-B, theverified registered user 4110 of FIG. 16) and the different registereduser to the verified registered user (e.g., the verified registered user4110 of FIG. 41A-B, the verified registered user 4110 of FIG. 16) may becommunicated to display.

In operation 2852, a hyperlink in the connection path of each of the atleast one registered users may be embedded through whom the connectionpath between the verified registered user (e.g., the verified registereduser 4110 of FIG. 41A-B, the verified registered user 4110 of FIG. 16)and the different registered user may be made. In operation 2854, eachregistered user associated e-mail addresses of individuals who are notregistered users may be stored and identified by each registered user asneighbors (e.g., a neighbor 2920 of FIG. 29).

In operation 2856, an invitation may be communicated to become a newuser (e.g., a user 2916 of FIG. 29) to neighbors (e.g., the neighbor2920 of FIG. 29) of the particular user. In operation 2858, anacceptance of the neighbor (e.g., the neighbor 2920 of FIG. 29) to whomthe invitation was sent may be processed. In operation 2860, theneighbor (e.g., the neighbor 2920 of FIG. 29) to a database and storingof the neighbor (e.g., the neighbor 2920 of FIG. 29), a user ID and theset of user IDs of registered users may be added who are directlyconnected to the neighbor (e.g., the neighbor 2920 of FIG. 29), the setof user IDs stored of the neighbor (e.g., the neighbor 2920 of FIG. 29)including at least the user ID of the verified registered user (e.g.,the verified registered user 4110 of FIG. 41A-B, the verified registereduser 4110 of FIG. 16).

FIG. 28E is a continuation of process flow of FIG. 28D showingadditional processes, according to one embodiment. In operation 2862,the verified registered user (e.g., the verified registered user 4110 ofFIG. 41A-B, the verified registered user 4110 of FIG. 16) that theinvitation to the neighbor (e.g., the neighbor 2920 of FIG. 29) has beenaccepted may be notified when the acceptance is processed.

In operation 2864, inputs from the neighbor (e.g., the neighbor 2920 ofFIG. 29) having descriptive data about the friend and storing the inputsin the database may be processed. In operation 2866, brief profiles ofregistered users, including a brief profile of the different registereduser may be communicated, to the verified registered user (e.g., theverified registered user 4110 of FIG. 41A-B, the verified registereduser 4110 of FIG. 16) for display, each of the brief profiles includingthe hyperlink to a corresponding full profile.

In operation 2868, the hyperlink selection from the verified registereduser (e.g., the verified registered user 4110 of FIG. 41A-B, theverified registered user 4110 of FIG. 16) may be processed, wherein,upon processing the hyperlink selection of the full profile of thedifferent registered user, the full profile of the different registereduser is communicated to the verified registered user (e.g., the verifiedregistered user 4110 of FIG. 41A-B, the verified registered user 4110 ofFIG. 16) for display.

In operation 2870, brief profiles of those registered users who may bemore than Nmax degrees of separation away from the verified registereduser (e.g., the verified registered user 4110 of FIG. 41A-B, theverified registered user 4110 of FIG. 16) may not communicated to theverified registered user (e.g., the verified registered user 4110 ofFIG. 41A-B, the verified registered user 4110 of FIG. 16) may be ensuredfor display.

In one embodiment, a neighborhood communication system 2950 isdescribed. This embodiment includes a privacy server 2900 to apply anaddress verification algorithm 2903 (e.g., using verify module 3006 ofFIG. 30) associated with each user of the online community (e.g., asshown in the social community view 3650 of FIG. 36 formed through theneighborhood network module as described in FIG. 38) to verify that eachuser lives at a residence associated with a claimable residentialaddress 4247 (e.g., using sub-modules of the claimable module 2910 asdescribed in FIG. 31) of an online community (e.g., as shown in thesocial community view 3650 of FIG. 36 formed through the neighborhoodnetwork module as described in FIG. 38) formed through a socialcommunity module 2906 of the privacy server 2900 using a processor 3902and a memory (e.g., as described in FIG. 39).

A network 2904, and a mapping server 2926 (e.g., providing global mapdata) communicatively coupled with the privacy server 2900 through thenetwork 2904 generate a latitudinal data and a longitudinal dataassociated with each claimable residential address 4247 (e.g., usingsub-modules of the claimable module 2910 as described in FIG. 31) of theonline community (e.g., as shown in the social community view 3650 ofFIG. 36 formed through the neighborhood network module as described inFIG. 38) associated with each user of the online community (e.g., asshown in the social community view 3650 of FIG. 36 formed through theneighborhood network module as described in FIG. 38) in this embodiment.

It will be appreciated that the neighborhood communication system 2950may operate the various multi-copters 100 of FIG. 1 in a peer-to-peertopology. Particularly, the peer-to-peer (P2P) networks formed in thevarious embodiments described in FIGS. 1-59 may include a type ofdecentralized and distributed network architecture in which individualmulti-copters (e.g., the multi-copters of FIG. 1) and client sidedevices (e.g., mobile devices of neighbors, desktop computers ofneighbors) in the network (e.g., “peers”) act as both suppliers andconsumers of resources, in contrast to the centralized client-servermodel where client nodes request access to resources provided by centralservers, according to one embodiment. Through a peer-to-peer methodologyof neighborhood multi-copters, each connected through a commoncentralized communication system (e.g., a cloud based communicationsystem), collisions between multi-copters can be minimized by relayingpositional information between a series of multi-copters and clientdevices presently in flight, according to one embodiment (e.g.,redundant paths and communications can be simultaneously handled). Inthis embodiment, controlling the multi-copter 100 functions may be areshared amongst multiple interconnected peers who each make a portion oftheir resources (such as processing power, disk storage or networkbandwidth) directly available to other network participants, without theneed for centralized coordination by servers, according to oneembodiment.

The privacy server 2900 automatically determines a set of accessprivileges in the online community (e.g., as shown in the socialcommunity view 3650 of FIG. 31 formed through the neighborhood networkmodule as described in FIG. 38) associated with each user of the onlinecommunity (e.g., as shown in the social community view 3650 of FIG. 36formed through the neighborhood network module as described in FIG. 38)by constraining access in the online community (e.g., as shown in thesocial community view 3650 of FIG. 36 formed through the neighborhoodnetwork module as described in FIG. 38) based on a neighborhood boundarydetermined using a Bezier curve algorithm 3040 of the privacy server2900 in this embodiment.

The privacy server 2900 (e.g., a hardware device of a globalneighborhood environment 1800) may transform the claimable residentialaddress 4247 (e.g., using sub-modules of the claimable module 2910 asdescribed in FIG. 31) into a claimed address upon an occurrence of anevent. The privacy server 2900 may instantiate the event when aparticular user 2916 is associated with the claimable residentialaddress 4247 (e.g., using sub-modules of the claimable module 2910 asdescribed in FIG. 31) based on a verification of the particular user2916 as living at a particular residential address (e.g., associatedwith the residence 2918 of FIG. 29) associated with the claimableresidential address 4247 (e.g., using sub-modules of the claimablemodule 2910 as described in FIG. 31) using the privacy server 2900. Theprivacy server 2900 may constrain the particular user 2916 tocommunicate through the online community (e.g., as shown in the socialcommunity view 3650 of FIG. 36 formed through the neighborhood networkmodule as described in FIG. 38) only with a database of neighbors 2928(e.g., such as the neighbor 2920 of FIG. 29 forming an occupant data)having verified addresses using the privacy server 2900. The privacyserver 2900 may define the database of neighbors 2928 (e.g., such as theneighbor 2920 of FIG. 29) as other users of the online community (e.g.,as shown in the social community view 3650 of FIG. 36 formed through theneighborhood network module as described in FIG. 38) that have eachverified their addresses in the online community (e.g., as shown in thesocial community view 3650 of FIG. 36 formed through the neighborhoodnetwork module as described in FIG. 38) using the privacy server 2900and/or which have each claimed residential addresses that are in athreshold radial distance 4219 from the claimed address of theparticular user 2916.

The privacy server 2900 may constrain the threshold radial distance 4219to be less than a distance of the neighborhood boundary using the Beziercurve algorithm 3040. The privacy server 2900 may permit theneighborhood boundary to take on a variety of shapes based on anassociated geographic connotation, a historical connotation, a politicalconnotation, and/or a cultural connotation of neighborhood boundaries.The privacy server 2900 may apply a database of constraints (e.g., thedatabases of FIG. 30 including the places database 3018) associated withneighborhood boundaries that are imposed on a map view of the onlinecommunity (e.g., as shown in the social community view 3650 of FIG. 36formed through the neighborhood network module as described in FIG. 38)when permitting the neighborhood boundary to take on the variety ofshapes.

The privacy server 2900 may generate a user-generated boundary in a formof a polygon describing geospatial boundaries defining the particularneighborhood when a first user of a particular neighborhood thatverifies a first residential address of the particular neighborhoodusing the privacy server 2900 prior to other users in that particularneighborhood verifying their addresses in that particular neighborhoodplaces a set of points defining the particular neighborhood using a setof drawing tools in the map view of the online community (e.g., as shownin the social community view 3650 of FIG. 36 formed through theneighborhood network module as described in FIG. 38). The privacy server2900 may optionally extend the threshold radial distance 4219 to anadjacent boundary of an adjacent neighborhood based a request of theparticular user 2916. The privacy server 2900 may generate a separatelogin to the online community (e.g., as shown in the social communityview 3650 of FIG. 36 formed through the neighborhood network module asdescribed in FIG. 38) designed to be usable by a police department, amunicipal agency, a neighborhood association, and/or a neighborhoodleader associated with the particular neighborhood.

The separate login may permit the police department, the municipalagency, the neighborhood association, and/or the neighborhood leader to:(1) invite residents of the particular neighborhood themselves (e.g.,see the user interface view of FIG. 22) using the privacy server 2900using a self-authenticating access code that permits new users thatenter the self-authenticating access code in the online community (e.g.,as shown in the social community view 3650 of FIG. 36 formed through theneighborhood network module as described in FIG. 38) to automaticallyjoin the particular neighborhood as verified users (e.g., the verifieduser 4110 of FIG. 41A), (2) generate a virtual neighborhood watch groupand/or an emergency preparedness group restricted to users verified inthe particular neighborhood using the privacy server 2900, (3) conducthigh value crime and/or safety related discussions from local policeand/or fire officials that is restricted to users verified in theparticular neighborhood using the privacy server 2900, (4) broadcastinformation across the particular neighborhood, and (5) receive and/ortrack neighborhood level membership and/or activity to identify leadersfrom the restricted group of users verified in the particularneighborhood using the privacy server 2900.

The privacy server 2900 may permit each of the restricted group of usersverified in the particular neighborhood using the privacy server 2900to: (1) share information about a suspicious activity that is likely toaffect several neighborhoods, (2) explain about a lost pet that mighthave wandered into an adjoining neighborhood, (3) rally support fromneighbors 2920 (e.g., such as the neighbor 2920 of FIG. 29) frommultiple neighborhoods to address civic issues, (4) spread informationabout events comprising a local theater production and/or a neighborhoodgarage sale, and/or (5) solicit advice and/or recommendations from therestricted group of users verified in the particular neighborhood and/oroptionally in the adjacent neighborhood.

The privacy server 2900 may flag a neighborhood feed from the particularneighborhood and/or optionally from the adjacent neighborhood as beinginappropriate. The privacy server 2900 may suspend users that repeatedlycommunicate self-promotional messages that are inappropriate as votedbased on a sensibility of any one of the verified users (e.g., theverified user 4110 of FIG. 41A) of the particular neighborhood and/oroptionally from the adjacent neighborhood. The privacy server 2900 maypersonalize which nearby neighborhoods that verified users (e.g., theverified user 4110 of FIG. 41A) are able to communicate through based ona request of the particular user 2916. The privacy server 2900 maypermit the neighborhood leader to communicate privately with leaders ofan adjoining neighborhood to plan and/or organize on behalf of an entireconstituency of verified users (e.g., a plurality of the verified user4110 of FIG. 41A) of the particular neighborhood associated with theneighborhood leader.

The privacy server 2900 may filter feeds to only display messages fromthe particular neighborhood associated with each verified user. Theprivacy server 2900 may restrict posts only in the particularneighborhood to verified users (e.g., the verified user 4110 of FIG.41A) having verified addresses within the neighborhood boundary (e.g.,the claim view 1550 of FIG. 15 describes a claiming process of anaddress). The address verification algorithm (e.g., using verify module3006 of FIG. 30) of the privacy server 2900 utilizes a set ofverification methods to perform verification of the particular user 2916through any of a: (1) a postcard verification method through which theprivacy server 2900 generates a physical postcard that is postal mailedto addresses of requesting users in the particular neighborhood and/orhaving a unique alphanumeric sequence in a form of an access codeprinted thereon which authenticates users that enter the access code toview and/or search privileges in the particular neighborhood of theonline community (e.g., as shown in the social community view 3650 ofFIG. 36 formed through the neighborhood network module as described inFIG. 38), (2) a credit card verification method through which theprivacy server 2900 verifies the claimable residential address 4247(e.g., using sub-modules of the claimable module 2910 as described inFIG. 31) when at least one a credit card billing address and/or a debitcard billing address is matched with an inputted address through anauthentication services provider, (3) a privately-published access codemethod through which the privacy server 2900 communicates to userprofiles of the police department, the municipal agency, theneighborhood association, and/or the neighborhood leader an instantaccess code that is printable at town hall meetings and/or gatheringssponsored by any one of the police department, the municipal agency, theneighborhood association, and/or the neighborhood leader, (4) a neighborvouching method through which the privacy server 2900 authenticates newusers when existing verified users (e.g., the verified user 4110 of FIG.41A) agree to a candidacy of new users in the particular neighborhood,(5) a phone verification method through which the privacy server 2900authenticates new users whose phone number is matched with an inputtedphone number through the authentication services provider, and (6) asocial security verification method through which the privacy server2900 authenticates new users whose social security number is matchedwith an inputted social security number through the authenticationservices provider.

The privacy server 2900 may initially set the particular neighborhood toa pilot phase status in which the online community (e.g., as shown inthe social community view 3650 of FIG. 36 formed through theneighborhood network module as described in FIG. 38) of the particularneighborhood is provisionally defined until a minimum number of usersverify their residential addresses in the particular neighborhoodthrough the privacy server 2900. The privacy server 2900 mayautomatically delete profiles of users that remain unverified after athreshold window of time. The neighborhood communication system 2950 maybe designed to create private websites to facilitate communication amongneighbors 2920 (e.g., such as the neighbor 2920 of FIG. 29) and/or buildstronger neighborhoods.

In another embodiment a method of a neighborhood communication system2950 is described. The method includes applying an address verificationalgorithm (e.g., using verify module 3006 of FIG. 30) associated witheach user of the online community (e.g., as shown in the socialcommunity view 3650 of FIG. 36 formed through the neighborhood networkmodule as described in FIG. 38) using a privacy server 2900, verifyingthat each user lives at a residence associated with a claimableresidential address 4247 (e.g., using sub-modules of the claimablemodule 2910 as described in FIG. 31) of an online community (e.g., asshown in the social community view 3650 of FIG. 36 formed through theneighborhood network module as described in FIG. 38) formed through asocial community module 2906 of the privacy server 2900 using aprocessor 3902 and a memory (e.g., as described in FIG. 39), generatinga latitudinal data and a longitudinal data associated with eachclaimable residential address 4247 (e.g., using sub-modules of theclaimable module 2910 as described in FIG. 31) of the online community(e.g., as shown in the social community view 3650 of FIG. 36 formedthrough the neighborhood network module as described in FIG. 38)associated with each user of the online community (e.g., as shown in thesocial community view 3650 of FIG. 36 formed through the neighborhoodnetwork module as described in FIG. 38), and determining a set of accessprivileges in the online community (e.g., as shown in the socialcommunity view 3650 of FIG. 36 formed through the neighborhood networkmodule as described in FIG. 38) associated with each user of the onlinecommunity (e.g., as shown in the social community view 3650 of FIG. 36formed through the neighborhood network module as described in FIG. 38)by constraining access in the online community (e.g., as shown in thesocial community view 3650 of FIG. 36 formed through the neighborhoodnetwork module as described in FIG. 38) based on a neighborhood boundarydetermined using a Bezier curve algorithm 3040 of the privacy server2900.

The method may transform the claimable residential address 4247 (e.g.,using sub-modules of the claimable module 2910 as described in FIG. 31)into a claimed address upon an occurrence of an event. The method mayinstantiate the event when a particular user 2916 is associated with theclaimable residential address 4247 (e.g., using sub-modules of theclaimable module 2910 as described in FIG. 31) based on a verificationof the particular user 2916 as living at a particular residentialaddress (e.g., associated with the residence 2918 of FIG. 29) associatedwith the claimable residential address 4247 (e.g., using sub-modules ofthe claimable module 2910 as described in FIG. 31) using the privacyserver 2900.

The method may constrain the particular user 2916 to communicate throughthe online community (e.g., as shown in the social community view 3650of FIG. 36 formed through the neighborhood network module as describedin FIG. 38) only with a database of neighbors 2928 (e.g., such as theneighbor 2920 of FIG. 29) having verified addresses using the privacyserver 2900. The method may define the database of neighbors 2928 (e.g.,such as the neighbor 2920 of FIG. 29) as other users of the onlinecommunity (e.g., as shown in the social community view 3650 of FIG. 36formed through the neighborhood network module as described in FIG. 38)that have each verified their addresses in the online community (e.g.,as shown in the social community view 3650 of FIG. 36 formed through theneighborhood network module as described in FIG. 38) using the privacyserver 2900 and/or which have each claimed residential addresses thatare in a threshold radial distance 4219 from the claimed address of theparticular user 2916.

The method may constrain the threshold radial distance 4219 to be lessthan a distance of the neighborhood boundary using the Bezier curvealgorithm 3040.

In addition, the method may define a neighborhood boundary to take on avariety of shapes based on an associated geographic connotation, ahistorical connotation, a political connotation, and/or a culturalconnotation of neighborhood boundaries. The method may apply a databaseof constraints (e.g., the databases of FIG. 30 including the placesdatabase 3018) associated with neighborhood boundaries that are imposedon a map view of the online community (e.g., as shown in the socialcommunity view 3650 of FIG. 36 formed through the neighborhood networkmodule as described in FIG. 38) when permitting the neighborhoodboundary to take on the variety of shapes.

The method may generate a user-generated boundary in a form of a polygondescribing geospatial boundaries defining the particular neighborhoodwhen a first user of a particular neighborhood that verifies a firstresidential address of the particular neighborhood using the privacyserver 2900 prior to other users in that particular neighborhoodverifying their addresses in that particular neighborhood places a setof points defining the particular neighborhood using a set of drawingtools in the map view of the online community (e.g., as shown in thesocial community view 3650 of FIG. 36 formed through the neighborhoodnetwork module as described in FIG. 38). The method may optionallyextend the threshold radial distance 4219 to an adjacent boundary of anadjacent neighborhood based a request of the particular user 2916.

The method may generate a separate login to the online community (e.g.,as shown in the social community view 3650 of FIG. 36 formed through theneighborhood network module as described in FIG. 38) designed to beusable by a police department, a municipal agency, a neighborhoodassociation, and/or a neighborhood leader associated with the particularneighborhood.

The method may permit the police department, the municipal agency, theneighborhood association, and/or the neighborhood leader to: (1) inviteresidents of the particular neighborhood themselves (e.g., see the userinterface view of FIG. 22) using the privacy server 2900 using aself-authenticating access code that permits new users that enter theself-authenticating access code in the online community (e.g., as shownin the social community view 3650 of FIG. 36 formed through theneighborhood network module as described in FIG. 38) to automaticallyjoin the particular neighborhood as verified users (e.g., the verifieduser 4110 of FIG. 41A), (2) generate a virtual neighborhood watch groupand/or an emergency preparedness group restricted to users verified inthe particular neighborhood using the privacy server 2900, (3) conducthigh value crime and/or safety related discussions from local policeand/or fire officials that is restricted to users verified in theparticular neighborhood using the privacy server 2900, (4) broadcastinformation across the particular neighborhood, and/or (5) receiveand/or track neighborhood level membership and/or activity to identifyleaders from the restricted group of users verified in the particularneighborhood using the privacy server 2900.

The method may permit each of the restricted group of users verified inthe particular neighborhood using the privacy server 2900 to: (1) shareinformation about a suspicious activity that is likely to affect severalneighborhoods, (2) explain about a lost pet that might have wanderedinto an adjoining neighborhood, (3) rally support from neighbors 2920(e.g., such as the neighbor 2920 of FIG. 29) from multiple neighborhoodsto address civic issues, (4) spread information about events comprisinga local theater production and/or a neighborhood garage sale, and/or (5)solicit advice and/or recommendations from the restricted group of usersverified in the particular neighborhood and/or optionally in theadjacent neighborhood.

The method may flag a neighborhood feed from the particular neighborhoodand/or optionally from the adjacent neighborhood as being inappropriate.The method may suspend users that repeatedly communicateself-promotional messages that are inappropriate as voted based on asensibility of any one of the verified users (e.g., the verified user4110 of FIG. 41A) of the particular neighborhood and/or optionally fromthe adjacent neighborhood. The method may personalize which nearbyneighborhoods that verified users (e.g., the verified user 4110 of FIG.41A) are able to communicate through based on a request of theparticular user 2916. The method may permit the neighborhood leader tocommunicate privately with leaders of an adjoining neighborhood to planand/or organize on behalf of an entire constituency of verified users ofthe particular neighborhood associated with the neighborhood leader.

The method may filter feeds to only display messages from the particularneighborhood associated with each verified user. The method may restrictposts only in the particular neighborhood to verified users (e.g., theverified user 4110 of FIG. 41A) having verified addresses within theneighborhood boundary (e.g., the claim view 1550 of FIG. 15 describes aclaiming process of an address). The method may utilize a set ofverification methods to perform verification of the particular user 2916through: (1) generating a physical postcard that is postal mailed toaddresses of requesting users in the particular neighborhood and/orhaving a unique alphanumeric sequence in a form of an access codeprinted thereon which authenticates users that enter the access code toview and/or search privileges in the particular neighborhood of theonline community (e.g., as shown in the social community view 3650 ofFIG. 36 formed through the neighborhood network module as described inFIG. 38). (2) verifying the claimable residential address 4247 (e.g.,using sub-modules of the claimable module 2910 as described in FIG. 31)when at least one a credit card billing address and/or a debit cardbilling address is matched with an inputted address through anauthentication services provider. (3) communicating to user profiles ofthe police department, the municipal agency, the neighborhoodassociation, and/or the neighborhood leader an instant access code thatis printable at town hall meetings and/or gatherings sponsored by anyone of the police department, the municipal agency, the neighborhoodassociation, and/or the neighborhood leader. (4) authenticating newusers when existing verified users (e.g., the verified user 4110 of FIG.41A) agree to a candidacy of new users in the particular neighborhood.(5) authenticating new users whose phone number is matched with aninputted phone number through the authentication services provider. (6)authenticating new users whose social security number is matched with aninputted social security number through the authentication servicesprovider.

The method may initially set the particular neighborhood to a pilotphase status in which the online community (e.g., as shown in the socialcommunity view 3650 of FIG. 36 formed through the neighborhood networkmodule as described in FIG. 38) of the particular neighborhood isprovisionally defined until a minimum number of users verify theirresidential addresses in the particular neighborhood through the privacyserver 2900. The method may automatically delete profiles of users thatremain unverified after a threshold window of time. The neighborhoodcommunication system 2950 may be designed to create private websites tofacilitate communication among neighbors 2920 (e.g., such as theneighbor 2920 of FIG. 29) and/or build stronger neighborhoods.

In yet another embodiment, another neighborhood communication system2950 is described. This embodiment includes a privacy server 2900 toapply an address verification algorithm (e.g., using verify module 3006of FIG. 30) associated with each user of the online community (e.g., asshown in the social community view 3650 of FIG. 36 formed through theneighborhood network module as described in FIG. 38) to verify that eachuser lives at a residence associated with a claimable residentialaddress 4247 (e.g., using sub-modules of the claimable module 2910 asdescribed in FIG. 31) of an online community (e.g., as shown in thesocial community view 3650 of FIG. 36 formed through the neighborhoodnetwork module as described in FIG. 38) formed through a socialcommunity module 2906 of the privacy server 2900 using a processor 3902and a memory (e.g., as described in FIG. 39), a network 2904, and amapping server 2926 (e.g., providing global map data) communicativelycoupled with the privacy server 2900 through the network 2904 togenerate a latitudinal data and a longitudinal data associated with eachclaimable residential address 4247 (e.g., using sub-modules of theclaimable module 2910 as described in FIG. 31) of the online community(e.g., as shown in the social community view 3650 of FIG. 36 formedthrough the neighborhood network module as described in FIG. 38)associated with each user of the online community (e.g., as shown in thesocial community view 3650 of FIG. 36 formed through the neighborhoodnetwork module as described in FIG. 38). The privacy server 2900automatically determines a set of access privileges in the onlinecommunity (e.g., as shown in the social community view 3650 of FIG. 36formed through the neighborhood network module as described in FIG. 38)associated with each user of the online community (e.g., as shown in thesocial community view 3650 of FIG. 36 formed through the neighborhoodnetwork module as described in FIG. 38) by constraining access in theonline community (e.g., as shown in the social community view 3650 ofFIG. 36 formed through the neighborhood network module as described inFIG. 38) based on a neighborhood boundary determined using a Beziercurve algorithm 3040 of the privacy server 2900 in this embodiment.

In addition, in this yet another embodiment the privacy server 2900transforms the claimable residential address 4247 (e.g., usingsub-modules of the claimable module 2910 as described in FIG. 31) into aclaimed address upon an occurrence of an event. The privacy server 2900instantiates the event when a particular user 2916 is associated withthe claimable residential address 4247 (e.g., using sub-modules of theclaimable module 2910 as described in FIG. 31) based on a verificationof the particular user 2916 as living at a particular residentialaddress (e.g., associated with the residence 2918 of FIG. 29) associatedwith the claimable residential address 4247 (e.g., using sub-modules ofthe claimable module 2910 as described in FIG. 31) using the privacyserver 2900 in this yet another embodiment. The privacy server 2900constrains the particular user 2916 to communicate through the onlinecommunity (e.g., as shown in the social community view 3650 of FIG. 36formed through the neighborhood network module as described in FIG. 38)only with a database of neighbors 2928 (e.g., such as the neighbor 2920of FIG. 29) having verified addresses using the privacy server 2900 inthis yet another embodiment. The privacy server 2900 defines thedatabase of neighbors 2928 (e.g., such as the neighbor 2920 of FIG. 29)as other users of the online community (e.g., as shown in the socialcommunity view 3650 of FIG. 36 formed through the neighborhood networkmodule as described in FIG. 38) that have each verified their addressesin the online community (e.g., as shown in the social community view3650 of FIG. 36 formed through the neighborhood network module asdescribed in FIG. 38) using the privacy server 2900 and which have eachclaimed residential addresses that are in a threshold radial distance4219 from the claimed address of the particular user 2916 in this yetanother embodiment.

FIG. 29 is a system view of a privacy server 2900 communicating withneighborhood(s) 2902A-N through a network 2904, an advertiser(s) 2924, amapping server 2926, an a database of neighbors 2928 (e.g., occupantdata), according to one embodiment. Particularly FIG. 29 illustrates theprivacy server 2900, the neighborhood 2902A-N, the network 2904,advertiser(s) 2924, mapping server 2926, and the database of neighbors2928 (e.g., occupant data), according to one embodiment. The privacyserver 2900 may contain a social community module 2906, a search module2908, a claimable module 2910, a commerce module 2912 and a map module2914. The neighborhood may include a user 2916, a community center 2921,a residence 2918, a neighbor 2920 and a business 2922, according to oneembodiment.

The privacy server 2900 may include any number of neighborhoods havingregistered users and/or unregistered users. The neighborhood(s) 2902 maybe a geographically localized community in a larger city, town, and/orsuburb. The network 2904 may be search engines, blogs, social networks,professional networks and static website that may unite individuals,groups and/or community. The social community module 2906 may generate abuilding creator in which the registered users may create and/or modifyempty claimable profiles (e.g., a claimable profile 4006 of FIG.40A-41B, a claimable profile 4102 of FIG. 41A, a claimable profile 1704of FIG. 17). The search module 2908 may include searching of informationof an individual, group and/or community.

The social community module 2906 (e.g., that applies the Bezier curvealgorithm 3040 of FIG. 30 using a series of modules working in concertas described in FIG. 30), as a function/module of the emergency responseserver, may determine the location of the user 2916, the distancebetween the user 2916 and other verified users (e.g., the verified user4110 of FIG. 41A), and the distance between the user 2916 and locationsof interest. With that information, the social community module 2906(e.g., that applies the Bezier curve algorithm 3040 of FIG. 30 using aseries of modules working in concert as described in FIG. 30) mayfurther determine which verified users (e.g., the verified user 4110 ofFIG. 41A) are within a predetermined vicinity of a user 2916. This setof verified users within the vicinity of another verified user may thenbe determined to be receptive to broadcasts transmitted by the user 2916and to be available as transmitters of broadcasts to the user 2916.

The social community module 2906 (e.g., that applies the Bezier curvealgorithm 3040 of FIG. 30 using a series of modules working in concertas described in FIG. 30) in effect may create a link between verifiedusers of the network 2904 that allows the users to communicate with eachother, and this link may be based on the physical distance between theusers as measured relative to a current geospatial location of thedevice (e.g., the device 1806, the device 1808 of FIG. 18) with aclaimed and verified (e.g., through a verification mechanism such as apostcard verification, a utility bill verification, and/or a vouching ofthe user with other users) non-transitory location (e.g., a homelocation, a work location) of the user and/or other users. In analternate embodiment, the transitory location of the user (e.g., theircurrent location, a current location of their vehicle and/or mobilephone) and/or the other users may also be used by the radial algorithm(e.g., the Bezier curve algorithm 3040 of FIG. 30) to determine anappropriate threshold distance for broadcasting a message.

Furthermore, the social community module 2906 (e.g., that applies theBezier curve algorithm 3040 of FIG. 30 using a series of modules workingin concert as described in FIG. 30) may automatically update a set ofpages associated with profiles of individuals and/or businesses thathave not yet joined the network based on preseeded address information.In effect, the social community module 2906 (e.g., that applies theBezier curve algorithm 3040 of FIG. 30 using a series of modules workingin concert as described in FIG. 30) may update preseeded pages in ageo-constrained radial distance from where a broadcast originates (e.g.,using an epicenter 4244 calculated from the current location of thedevice (e.g., the device 1806, the device 1808 of FIG. 18) (e.g., amobile version of the device 1806 of FIG. 18 (e.g., a mobile phone, atablet computer) with information about the neighborhood broadcast data.In effect, through this methodology, the social community module 2906(e.g., that applies the Bezier curve algorithm 3040 of FIG. 30 using aseries of modules working in concert as described in FIG. 30) may leave‘inboxes’ and/or post ‘alerts’ on pages created for users that have notyet signed up based on a confirmed address of the users through a publicand/or a private data source (e.g., from Infogroup®, from a white pagedirectory, etc.).

The social community module 2906 (e.g., that applies the Bezier curvealgorithm 3040 of FIG. 30 using a series of modules working in concertas described in FIG. 30) of the privacy server 2900 may be differentfrom previous implementations because it is the first implementation tosimulate the experience of local radio transmission between individualsusing the internet and non-radio network technology by basing theirnetwork broadcast range on the proximity of verified users to oneanother, according to one embodiment.

The Bezier curve algorithm 3040 may operate as follows, according to oneembodiment. The radial algorithm (e.g., the Bezier curve algorithm 3040of FIG. 30) may utilize a radial distribution function (e.g., a paircorrelation function)g(r)

In the neighborhood communication system 2950. The radial distributionfunction may describe how density varies as a function of distance froma user 2916, according to one embodiment.

If a given user 2916 is taken to be at the origin O (e.g., the epicenter4244), and ifρp=N/Vis the average number density of recipients (e.g., other users of theneighborhood communication system 2950 such as neighbors 2920 of FIG.29) in the neighborhood communication system 2950, then the localtime-averaged density at a distance r from O isρg(r)according to one embodiment. This simplified definition may hold for ahomogeneous and isotropic type of recipients (e.g., other users of theneighborhood communication system 2950 such as neighbors 2920 of FIG.29), according to one embodiment of the Bezier curve algorithm 3040.

A more anisotropic distribution (e.g., exhibiting properties withdifferent values when measured in different directions) of therecipients (e.g., other users of the neighborhood communication system2950 such as neighbors 2920 of FIG. 29) will be described below,according to one embodiment of the Bezier curve algorithm 3040. Insimplest terms it may be a measure of the probability of finding arecipient at a distance of r away from a given user 2916, relative tothat for an ideal distribution scenario, according to one embodiment.The anisotropic algorithm involves determining how many recipients(e.g., other users of the neighborhood communication system 2950 such asneighbors 2920 of FIG. 29) are within a distance of r and r+dr away fromthe user 2916, according to one embodiment. The Bezier curve algorithm3040 may be determined by calculating the distance between all userpairs and binning them into a user histogram, according to oneembodiment.

The histogram may then be normalized with respect to an ideal user atthe origin o, where user histograms are completely uncorrelated,according to one embodiment. For three dimensions (e.g., such as abuilding representation in the privacy server 2900 in which there aremultiple residents in each floor), this normalization may be the numberdensity of the system multiplied by the volume of the spherical shell,which mathematically can be expressed asg(r)_(I)=4πr ² ρdr,where ρ may be the user density, according to one embodiment of theBezier curve algorithm 3040.

The radial distribution function of the Bezier curve algorithm 3040 canbe computed either via computer simulation methods like the Monte Carlomethod, or via the Ornstein-Zernike equation, using approximativeclosure relations like the Percus-Yevick approximation or theHypernetted Chain Theory, according to one embodiment.

This may be important because by confining the broadcast reach of averified user in the neighborhood communication system 2950 to aspecified range, the social community module 2906 (e.g., that appliesthe Bezier curve algorithm 3040 of FIG. 30 using a series of modulesworking in concert as described in FIG. 30) may replicate the experienceof local radio broadcasting and enable verified users to communicateinformation to their immediate neighbors as well as receive informationfrom their immediate neighbors in areas that they care about, accordingto one embodiment. Such methodologies can be complemented withhyperlocal advertising targeted to potential users of the privacy server2900 on preseeded profile pages and/or active user pages of the privacyserver 2900. Advertisement communications thus may become highlyspecialized and localized resulting in an increase in their value andinterest to the local verified users of the network through the privacyserver 2900. For example, advertisers may wish to communicate helpfulhome security devices to a set of users located in a geospatial areawith a high concentration of home break-in broadcasts.

The social community module 2906 (e.g., that applies the Bezier curvealgorithm 3040 of FIG. 30 using a series of modules working in concertas described in FIG. 30) may also have wide application as it may solvethe problem of trying to locate a receptive audience to a verifieduser's broadcasts, whether that broadcast may a personal emergency, anone's personal music, an advertisement for a car for sale, asolicitation for a new employee, and/or a recommendation for a goodrestaurant in the area. This social community module 2906 (e.g., thatapplies the Bezier curve algorithm 3040 of FIG. 30 using a series ofmodules working in concert as described in FIG. 30) may eliminateunnecessarily broadcasting that information to those who are notreceptive to it, both as a transmitter and as a recipient of thebroadcast. The radial algorithm (e.g., the Bezier curve algorithm 3040of FIG. 30) saves both time (which may be critical and limited in anemergency context) and effort of every user involved by transmittinginformation only to areas that a user cares about, according to oneembodiment.

In effect, the radial algorithm (e.g., the Bezier curve algorithm 3040of FIG. 30) of the emergency response server enables users to notifypeople around locations that are cared about (e.g., around where theylive, work, and/or where they are physically located). In oneembodiment, the user 2916 can be provided ‘feedback’ and/or acommunication that the neighbor 2920 may be responding to the emergencyafter the neighborhood broadcast data may be delivered to the recipients(e.g., other users of the neighborhood communication system 2950 such asneighbors 2920 of FIG. 29) and/or to the neighborhood services using thesocial community module 2906 (e.g., that applies the Bezier curvealgorithm 3040 of FIG. 30 using a series of modules working in concertas described in FIG. 30) of the privacy server 2900. For example, afterthe neighborhood broadcast data may be delivered, the device (e.g., thedevice 1806, the device 1808 of FIG. 18) (e.g., a mobile version of thedevice 1806 of FIG. 18 (e.g., a mobile phone, a tablet computer)) maydisplay a message saying: “3256 neighbors around a 1 radius from youhave been notified on their profile pages of your crime broadcast inMenlo Park and 4 people are responding” and/or “8356 neighbors and twohospitals around a 2.7 radius from you have been notified of yourmedical emergency.”

The various embodiments described herein of the privacy server 2900using the social community module 2906 (e.g., that applies the Beziercurve algorithm 3040 of FIG. 30 using a series of modules working inconcert as described in FIG. 30) may solve a central problem of internetradio service providers (e.g., Pandora) by retaining culturalsignificance related to a person's locations of association. Forexample, the social community module 2906 (e.g., that applies the Beziercurve algorithm 3040 of FIG. 30 using a series of modules working inconcert as described in FIG. 30) may be used to ‘create’ new radiostations, television stations, and/or mini alert broadcasts to ageospatially constrained area on one end, and provide a means for those‘tuning in’ to consume information posted in a geospatial area that thelistener cares about and/or associates themselves with. The informationprovided can be actionable in that the user 2916 may be able to securenew opportunities through face to face human interaction and physicalmeeting not otherwise possible in internet radio scenarios.

The radial algorithm (e.g., the Bezier curve algorithm 3040 of FIG. 30)may be a set of instructions that may enable users (e.g., verifiedusers, non-verified users) of the Nextdoor.com and Fatdoor.com websitesand applications to broadcast their activities (e.g., garage sale,t-shirt sale, crime alert) to surrounding neighbors within a claimedneighborhood and to guests of a claimed neighborhood, according to oneembodiment. The radial algorithm (e.g., the Bezier curve algorithm 3040of FIG. 30) may be new because current technology does not allow forusers of a network (e.g., Nextdoor.com, Fatdoor.com) to locallybroadcast their activity to a locally defined geospatial area. With theradial algorithm (e.g., the Bezier curve algorithm 3040 of FIG. 30),users of the network may communicate with one another in a locallydefined manner, which may present more relevant information andactivities, according to one embodiment. For example, if a verified userof the network broadcasts an emergency, locally defined neighbors of theverified user may be much more interested in responding than if theyobserved an emergency on a general news broadcast on traditional radio,according to one embodiment. The social community module 2906 may solvethe problem of neighbors living in the locally defined geospatial areawho don't typically interact, and allows them to connect within avirtual space that did not exist before, according to one embodiment.Community boards (e.g., stolen or missing item boards) may have been aprimary method of distributing content in a surrounding neighborhoodeffectively prior to the disclosures described herein. However, therewas no way to easily distribute content related to exigent circumstancesand/or with urgency in a broadcast-like manner to those listening arounda neighborhood through mobile devices until the various embodimentsapplying the social community module 2906 as described herein.

A Bezier curve algorithm 3040 may be a method of calculating a sequenceof operations, and in this case a sequence of radio operations,according to one embodiment. Starting from an initial state and initialinput, the Bezier curve algorithm 3040 describes a computation that,when executed, proceeds through a finite number of well-definedsuccessive states, eventually producing radial patterned distribution(e.g., simulating a local radio station), according to one embodiment.

The privacy server 2900 may solve technical challenges through thesocial community module 2906 (e.g., that applies the Bezier curvealgorithm 3040 of FIG. 30 using a series of modules working in concertas described in FIG. 30) by implementing a vigorous screening process toscreen out any lewd or vulgar content in one embodiment. For example,what may be considered lewd content sometimes could be subjective, andverified users could argue that the operator of the privacy server 2900is restricting their constitutional right to freedom of speech (e.g., ifthe emergency response server is operated by a government entity)through a crowd-moderation capability enabled by the social communitymodule 2906 (e.g., that applies the Bezier curve algorithm 3040 of FIG.30 using a series of modules working in concert as described in FIG.30), according to one embodiment. In one embodiment, verified users maysign an electronic agreement to screen their content and agree that theneighborhood communication system 2950 may delete any content that itdeems inappropriate for broadcasting, through the social communitymodule 2906 (e.g., that applies the Bezier curve algorithm 3040 of FIG.30 using a series of modules working in concert as described in FIG. 30)according to one embodiment. For example, it may be determined that alost item such as a misplaced set of car keys does not qualify as an“emergency” that should be broadcast.

The social community module 2906 (e.g., that applies the Bezier curvealgorithm 3040 of FIG. 30 using a series of modules working in concertas described in FIG. 30), in addition to neighborhood broadcasts (e.g.,such as emergency broadcasts), may allow verified users to create andbroadcast their own radio show, e.g., music, talk show, commercial,instructional contents, etc., and to choose their neighborhood(s) forbroadcasting based on a claimed location, according to one embodiment.The social community module 2906 (e.g., that applies the Bezier curvealgorithm 3040 of FIG. 30 using a series of modules working in concertas described in FIG. 30) may allow users to choose the neighborhoodsthat they would want to receive the broadcasts, live and recordedbroadcasts, and/or the types and topics (e.g., minor crimes, propertycrimes, medical emergencies) of broadcasts that interest them.

The social community module 2906 (e.g., that applies the Bezier curvealgorithm 3040 of FIG. 30 using a series of modules working in concertas described in FIG. 30) based approach of the privacy server 2900 maybe a completely different concept from the currently existingneighborhood (e.g., geospatial) social networking options. The socialcommunity module 2906 (e.g., that applies the Bezier curve algorithm3040 of FIG. 30 using a series of modules working in concert asdescribed in FIG. 30) may also allow the user to create his/her ownradio station, television station and/or other content such as theneighborhood broadcast data and distribute this content around locationsto users and preseeded profiles around them. For example, the user maywish to broadcast their live reporting of a structure fire or intervieweye-witnesses to a robbery. The social community module 2906 (e.g., thatapplies the Bezier curve algorithm 3040 of FIG. 30 using a series ofmodules working in concert as described in FIG. 30) can allow verifiedusers to create their content and broadcast in the selected geospatialarea. It also allows verified listeners to listen to only the relevantlocal broadcasts of their choice.

The social community module 2906 (e.g., that applies the Bezier curvealgorithm 3040 of FIG. 30 using a series of modules working in concertas described in FIG. 30) may be important because it may provide anyverified user the opportunity to create his/her own radial broadcastmessage (e.g., can be audio, video, pictorial and/or textual content)and distribute this content to a broad group. Social community module2906 (e.g., that applies the Bezier curve algorithm 3040 of FIG. 30using a series of modules working in concert as described in FIG. 30)may also allow verified listeners to listen to any missed livebroadcasts through the prerecorded features, according to oneembodiment. Through this, the social community module 2906 (e.g., thatapplies the Bezier curve algorithm 3040 of FIG. 30 using a series ofmodules working in concert as described in FIG. 30) changes the waysocial networks (e.g., Nextdoor®, Fatdoor®, Facebook®, Path®, etc.)operate by enabling location centric broadcasting to regions that a usercares about, according to one embodiment. Social community module 2906(e.g., that applies the Bezier curve algorithm 3040 of FIG. 30 using aseries of modules working in concert as described in FIG. 30) may solvea technical challenge by defining ranges based on a type of an emergencytype, a type of neighborhood, and/or boundary condition of aneighborhood by analyzing whether the neighborhood broadcast data may beassociated with a particular kind of recipient, a particularneighborhood, a temporal limitation, and/or through another criteria.

By using the social community module 2906 (e.g., that applies the Beziercurve algorithm 3040 of FIG. 30 using a series of modules working inconcert as described in FIG. 30) of the privacy server 2900 the user2916 may be able to filter irrelevant offers and information provided bybroadcasts. In one embodiment, only the broadcasting user (e.g., theuser 2916) may be a verified user to create accountability for aparticular broadcast and/or credibility of the broadcaster. In thisembodiment, recipients (e.g., other users of the neighborhoodcommunication system 2950 such as neighbors 2920 of FIG. 29) of thebroadcast may not need to be verified users of the emergency responsenetwork. By directing traffic and organizing the onslaught ofbroadcasts, the social community module 2906 (e.g., that applies theBezier curve algorithm 3040 of FIG. 30 using a series of modules workingin concert as described in FIG. 30) of the privacy server 2900 may beable to identify the origins and nature of each group of incominginformation and locate recipients (e.g., other users of the neighborhoodcommunication system 2950 such as neighbors 2920 of FIG. 29) that arerelevant/interested in the neighborhood broadcast data, maximizing theeffective use of each broadcast. For example, the neighbor 2920 may beable to specify that they own a firearm so that they would be a relevantneighbor 2920 for broadcast data to respond to a school shooting. Inanother example, the neighbor 2920 may specify that they are a medicalprofessional (e.g., paramedic, physician) such that they may receivemedical emergency broadcasts, according to one embodiment.

The social community module 2906 (e.g., that applies the Bezier curvealgorithm 3040 of FIG. 30 using a series of modules working in concertas described in FIG. 30) of the privacy server 2900 may process theinput data from the device (e.g., the device 1806, the device 1808 ofFIG. 18) (e.g., a mobile version of the device 1806 of FIG. 18 (e.g., amobile phone, a tablet computer)) in order to identify whichnotification(s) to broadcast to which individual(s). This may beseparate from a traditional radio broadcast as it not onlygeographically constrains broadcasters and recipients (e.g., other usersof the neighborhood communication system 2950 such as neighbors 2920 ofFIG. 29) but also makes use of user preferences in order to allowbroadcasters to target an optimal audience and allow recipients (e.g.,other users of the neighborhood communication system 2950 such asneighbors 2920 of FIG. 29) to alter and customize what they consume. Theuser 2916 may associate him/herself with a non-transitory address inorder to remain constantly connected to their neighborhood and/orneighbors even when they themselves or their neighbors are away. TheBezier curve algorithm 3040 may be also unique from a neighborhoodsocial network (e.g., the privacy server 2900) as it permits users tobroadcast emergencies, information, audio, video etc. to other users,allowing users to create their own stations.

In order to implement the social community module 2906 (e.g., thatapplies the Bezier curve algorithm 3040 of FIG. 30 using a series ofmodules working in concert as described in FIG. 30), geospatial data mayneed to be collected and amassed in order to create a foundation onwhich users may sign up and verify themselves by claiming a specificaddress, associating themselves with that geospatial location. Thesocial community module 2906 (e.g., that applies the Bezier curvealgorithm 3040 of FIG. 30 using a series of modules working in concertas described in FIG. 30) may then be able to utilize the geospatialdatabase 4222 to filter out surrounding noise and deliver only relevantdata to recipients (e.g., other users of the neighborhood communicationsystem 2950 such as neighbors 2920 of FIG. 29). In order to accomplishthis, the social community module 2906 (e.g., that applies the Beziercurve algorithm 3040 of FIG. 30 using a series of modules working inconcert as described in FIG. 30) may be able to verify the reliabilityof geospatial coordinates, time stamps, and user information associatedwith the device (e.g., the device 1806, the device 1808 of FIG. 18)(e.g., a mobile version of the device 1806 of FIG. 18 (e.g., a mobilephone, a tablet computer)). In addition, threshold geospatial radii,private neighborhood boundaries, and personal preferences may beestablished in the privacy server 2900 and accommodated using the socialcommunity module 2906 (e.g., that applies the Bezier curve algorithm3040 of FIG. 30 using a series of modules working in concert asdescribed in FIG. 30). The geospatial database 4222 may work in concertwith the social community module 2906 (e.g., that applies the Beziercurve algorithm 3040 of FIG. 30 using a series of modules working inconcert as described in FIG. 30) to store, organize, and managebroadcasts, pushpins, user profiles, preseeded user profiles, metadata,and epicenter 4244 locations associated with the privacy server 2900(e.g., a neighborhood social network such as Fatdoor.com, Nextdoor.com).

The Bezier curve algorithm 3040 may be used to calculate relativedistances between each one of millions of records as associated witheach placed geo-spatial coordinate in the privacy server 2900 (e.g., aneighborhood social network such as Fatdoor.com, Nextdoor.com).Calculations of relative distance between each geospatial coordinate canbe a large computational challenge because of the high number of reads,writes, modify, and creates associated with each geospatial coordinateadded to the privacy server 2900 and subsequent recalculations ofsurrounding geospatial coordinates associated with other users and/orother profile pages based a relative distance away from a newly addedset of geospatial coordinates (e.g., associated with the neighborhoodbroadcast data and/or with other pushpin types). To overcome thiscomputational challenge, the radial algorithm (e.g., the Bezier curvealgorithm 3040 of FIG. 30) may leverage a massively parallel computingarchitecture 4246 through which processing functions are distributedacross a large set of processors accessed in a distributed computingsystem 4248 through the network 2904.

In order to achieve the utilization of the massively parallel computingarchitecture 4246 in a context of a radial distribution function of aprivacy server 2900, a number of technical challenges have been overcomein at least one embodiment. Particularly, the social community module2906 constructs a series of tables based on an ordered geospatialranking based on frequency of interaction through a set of ‘n’ number ofusers simultaneously interacting with the privacy server 2900, in onepreferred embodiment. In this manner, sessions of access between theprivacy server 2900 and users of the privacy server 2900 (e.g., the user2916) may be monitored based on geospatial claimed areas of the user(e.g., a claimed work and/or home location of the user), and/or apresent geospatial location of the user. In this manner, tablesassociated with data related to claimed geospatial areas of the userand/or the present geospatial location of the user may be anticipatorilycached in the memory 2924 to ensure that a response time of the privacyserver 2900 may be not constrained by delays caused by extraction,retrieval, and transformation of tables that are not likely to berequired for a current and/or anticipated set of sessions between usersand the privacy server 2900.

In a preferred embodiment, an elastic computing environment may be usedby the social community module 2906 to provide for increase/decreases ofcapacity within minutes of a database function requirement. In thismanner, the social community module 2906 can adapt to workload changesbased on number of requests of processing simultaneous and/or concurrentrequests associated with neighborhood broadcast data by provisioning andde-provisioning resources in an autonomic manner, such that at eachpoint in time the available resources match the current demand asclosely as possible.

The social community module 2906 (e.g., that applies the Bezier curvealgorithm 3040 of FIG. 30 using a series of modules working in concertas described in FIG. 30) may be a concept whereby a server communicatingdata to a dispersed group of recipients (e.g., other users of theneighborhood communication system 2950 such as neighbors 2920 of FIG.29) over a network 2904, which may be an internet protocol based widearea network (as opposed to a network communicating by radio frequencycommunications) communicates that data only to ageospatially-constrained group of recipients (e.g., other users of theneighborhood communication system 2950 such as neighbors 2920 of FIG.29). The social community module 2906 (e.g., that applies the Beziercurve algorithm 3040 of FIG. 30 using a series of modules working inconcert as described in FIG. 30) may apply a geospatial constraintrelated to a radial distance away from an origin point, or a constraintrelated to regional, state, territory, county, municipal, neighborhood,building, community, district, locality, and/or other geospatialboundaries.

The social community module 2906 (e.g., that applies the Bezier curvealgorithm 3040 of FIG. 30 using a series of modules working in concertas described in FIG. 30) may be new as applied to data traveling overwide area networks using internet protocol topology in a geospatialsocial networking and commerce context, according to one embodiment.While radio broadcasts, by their nature, are transmitted in a radialpattern surrounding the origin point, there may be no known mechanismfor restricting access to the data only to verified users of a servicesubscribing to the broadcast. As applied to wired computer networks,while techniques for applying geospatial constraints have been appliedto search results, and to other limited uses, there has as yet been noapplication of geospatial constraint as applied to the variousembodiments described herein using the social community module 2906(e.g., that applies the Bezier curve algorithm 3040 of FIG. 30 using aseries of modules working in concert as described in FIG. 30).

The social community module 2906 (e.g., that applies the Bezier curvealgorithm 3040 of FIG. 30 using a series of modules working in concertas described in FIG. 30) may be roughly analogous to broadcast radiocommunications such as a) in broadcast radio, b) in wireless computernetworking, and c) in mobile telephony. However, all of these systemsbroadcast their information promiscuously, making the data transmittedavailable to anyone within range of the transmitter who may be equippedwith the appropriate receiving device. In contrast, the social communitymodule 2906 (e.g., that applies the Bezier curve algorithm 3040 of FIG.30 using a series of modules working in concert as described in FIG. 30)herein describes a system in which networks are used to transmit data ina selective manner in that information may be distributed around aphysical location of homes or businesses in areas of interest/relevancy.

The social community module 2906 (e.g., that applies the Bezier curvealgorithm 3040 of FIG. 30 using a series of modules working in concertas described in FIG. 30) may solve a problem of restricting datatransmitted over networks to specific users who are within a specifieddistance from the individual who originates the data. In a broad sense,by enabling commerce and communications that are strictly limited withindefined neighborhood boundaries, the social community module 2906 (e.g.,that applies the Bezier curve algorithm 3040 of FIG. 30 using a seriesof modules working in concert as described in FIG. 30) may enable theprivacy server 2900 (e.g., a neighborhood social network such asFatdoor.com, Nextdoor.com) communications, attacking the serious socialconditions of anonymity and disengagement in community that afflict thenation and, increasingly, the world.

The social community module 2906 (e.g., that applies the Bezier curvealgorithm 3040 of FIG. 30 using a series of modules working in concertas described in FIG. 30) may comprise one or more modules that instructthe privacy server 2900 to restrict the broadcasting of the neighborhoodbroadcast data to one or more parts of the geospatial area 117. Forexample, in the embodiment of FIG. 29, the social community module 2906(e.g., that applies the Bezier curve algorithm 3040 of FIG. 30 using aseries of modules working in concert as described in FIG. 30) mayinstruct the privacy server 2900 to broadcast the neighborhood broadcastdata to the recipients (e.g., other users of the neighborhoodcommunication system 2950 such as neighbors 2920 of FIG. 29) but not tothe area outside the threshold radial distance 4215.

In one or more embodiments, the social community module 2906 (e.g., thatapplies the Bezier curve algorithm 3040 of FIG. 30 using a series ofmodules working in concert as described in FIG. 30) may allow theprivacy server 2900 to function in manner that simulates a traditionalradio broadcast (e.g., using a radio tower to transmit a radio frequencysignal) in that both the privacy server 2900 and the radio broadcast arerestricted in the geospatial scope of the broadcast transmission. In oneor more embodiments, the social community module 2906 (e.g., thatapplies the Bezier curve algorithm 3040 of FIG. 30 using a series ofmodules working in concert as described in FIG. 30) may prevent thebroadcast of the neighborhood broadcast data to any geospatial area towhich the user 2916 does not wish to transmit the neighborhood broadcastdata, and/or to users that have either muted and/or selectivelysubscribed to a set of broadcast feeds.

The social community module 2906 (e.g., that applies the Bezier curvealgorithm 3040 of FIG. 30 using a series of modules working in concertas described in FIG. 30) may analyze the neighborhood broadcast data todetermine which recipients (e.g., other users of the neighborhoodcommunication system 2950 such as neighbors 2920 of FIG. 29) may receivenotification data 4212 within the threshold radial distance 4219 (e.g.,set by the user 2916 and/or auto calculated based on a type of emergencyposting). The social community module 2906 (e.g., that applies theBezier curve algorithm 3040 of FIG. 30 using a series of modules workingin concert as described in FIG. 30) may use a variety of parameters,including information associated with the neighborhood broadcast data(e.g., location of the broadcast, type of broadcast, etc.) to determinethe threshold radial distance 4219.

The social community module 2906 (e.g., that applies the Bezier curvealgorithm 3040 of FIG. 30 using a series of modules working in concertas described in FIG. 30) may also determine which verified addressesassociated with recipients (e.g., other users of the neighborhoodcommunication system 2950 such as neighbors 2920 of FIG. 29) havingverified user profiles are located within the threshold radial distance4219. The social community module 2906 (e.g., that applies the Beziercurve algorithm 3040 of FIG. 30 using a series of modules working inconcert as described in FIG. 30) may then broadcast the notificationdata 4212 to the profiles and/or mobile devices of the verified usershaving verified addresses within the threshold radial distance 4219.

The social community module 2906 (e.g., that applies the Bezier curvealgorithm 3040 of FIG. 30 using a series of modules working in concertas described in FIG. 30) may therefore simulate traditional radiobroadcasting (e.g., from a radio station transmission tower) over the IPnetwork. Thus, the social community module 2906 (e.g., that applies theBezier curve algorithm 3040 of FIG. 30 using a series of modules workingin concert as described in FIG. 30) may allow the broadcast to includeinformation and data that traditional radio broadcasts may not be ableto convey, for example geospatial coordinates and/or real-timebi-directional communications. Additionally, the social community module2906 (e.g., that applies the Bezier curve algorithm 3040 of FIG. 30using a series of modules working in concert as described in FIG. 30)may allow individual users low-entry broadcast capability without resortto expensive equipment and/or licensing by the Federal CommunicationsCommission (FCC).

Another advantage of this broadcast via the social community module 2906(e.g., that applies the Bezier curve algorithm 3040 of FIG. 30 using aseries of modules working in concert as described in FIG. 30) may bethat it may bypass obstructions that traditionally disrupt radio wavessuch as mountains and/or atmospheric disturbances. Yet another advantageof the social community module 2906 (e.g., that applies the Bezier curvealgorithm 3040 of FIG. 30 using a series of modules working in concertas described in FIG. 30) may be that it may expand the physical distanceof broadcast capability without resort to the expense ordinarilyassociated with generating powerful carrier signals. In yet anotheradvantage, the social community module 2906 (e.g., that applies theBezier curve algorithm 3040 of FIG. 30 using a series of modules workingin concert as described in FIG. 30) may allow for almost unlimitedchannels and/or stations as compared to traditional radio where only anarrow band of electromagnetic radiation has been appropriated for useamong a small number of entities by government regulators (e.g., theFCC).

The claimable module 2910 may enable the registered users to createand/or update their information. A ‘claimable’ (e.g., may be enabledthrough the claimable module 2910) can be defined as a perpetualcollective work of many authors. Similar to a blog in structure andlogic, a claimable allows anyone to edit, delete or modify content thathas been placed on the Web site using a browser interface, including thework of previous authors. In contrast, a blog (e.g., or a social networkpage), typically authored by an individual, may not allow visitors tochange the original posted material, only add comments to the originalcontent. The term claimable refers to either the web site or thesoftware used to create the site. The term ‘claimable’ also implies fastcreation, ease of creation, and community approval in many softwarecontexts (e.g., claimable means “quick” in Hawaiian).

The commerce module 2912 may provide an advertisement system to abusiness that may enable the users to purchase location in theneighborhood(s) 2902. The map module 2914 may be indulged in study,practice, representing and/or generating maps, or globes. The user 2916may be an individuals and/or households that may purchase and/or usegoods and services and/or be an active member of any group or communityand/or resident and/or a part of any neighborhood(s) 2902. The residence2918 may be a house, a place to live and/or like a nursing home in aneighborhood(s) 2902.

The community center 2921 may be public locations where members of acommunity may gather for group activities, social support, publicinformation, and other purposes. The business 2922 may be a customerservice, finance, sales, production, communications/public relationsand/or marketing organization that may be located in the neighborhood(s)2902. The advertiser(s) 2924 may be an individual and/or a firm drawingpublic who may be responsible in encouraging the people attention togoods and/or services by promoting businesses, and/or may performthrough a variety of media. The mapping server 2926 may contain thedetails/maps of any area, region and/or neighborhood. The socialcommunity module 2906 of the privacy server 2900 may communicate withthe neighborhood(s) 2902 through the network 2904 and/or the searchmodule 2908. The social community module 2906 of the privacy server 2900may communicate with the advertiser(s) 2924 through the commerce module,the database of neighbors 2928 (e.g., occupant data) and/or mappingserver 2926 through the map module 2914.

For example, the neighborhoods 2902A-N may have registered users and/orunregistered users of a privacy server 2900. Also, the social communitymodule 2906 of the privacy server 2900 may generate a building creator(e.g., building builder 1602 of FIG. 16) in which the registered usersmay create and/or modify empty claimable profiles, building layouts,social network pages, and/or floor levels structures housing residentsand/or businesses in the neighborhood.

In addition, the claimable module 2910 of the privacy server 2900 mayenable the registered users to create a social network page ofthemselves, and/or may edit information associated with the unregisteredusers identifiable through a viewing of physical properties in which,the unregistered users reside when the registered users have knowledgeof characteristics associated with the unregistered users.

Furthermore, the search module 2908 of the privacy server 2900 mayenable a people search (e.g., the people search widget 3100 of FIG. 31),a business search (e.g., the business search module 3102 of FIG. 31),and/or a category search (e.g., the category search widget 3104 of FIG.31) of any data in the social community module 2906 and/or may enableembedding of any content in the privacy server 2900 in other searchengines, blogs, social networks, professional networks and/or staticwebsites.

The commerce module 2912 of the privacy server 2900 may provide anadvertisement system to a business who purchase their location in theprivacy server 2900 in which the advertisement may be viewableconcurrently with a map indicating a location of the business, and/or inwhich revenue may be attributed to the privacy server 2900 when theregistered users and/or the unregistered users click-in on asimultaneously displayed data of the advertisement along with the mapindicating a location of the business.

Moreover, a map module 2914 of the privacy server 2900 may include a mapdata associated with a satellite data (e.g., generated by the satellitedata module 3400 of FIG. 34) which may serve as a basis of rendering themap in the privacy server 2900 and/or which includes a simplified mapgenerator which may transform the map to a fewer color and/or locationcomplex form using a parcel data which identifies some residence, civic,and/or business locations in the satellite data.

In addition, a first instruction set may enable a social network toreside above a map data, in which the social network may be associatedwith specific geographical locations identifiable in the map data. Also,a second instruction set integrated with the first instruction set mayenable users of the social network to create profiles of other peoplethrough a forum which provides a free form of expression of the userssharing information about any entities and/or people residing in anygeographical location identifiable in the satellite map data, and/or toprovide a technique of each of the users to claim a geographic location(e.g., a geographic location 29024 of FIG. 40A) to control content intheir respective claimed geographic locations (e.g., a geographiclocation 29024 of FIG. 40A).

Furthermore, a third instruction set integrated with the firstinstruction set and the second instruction set may enable searching ofpeople in the privacy server 2900 by indexing each of the data shared bythe user 2916 of any of the people and/or the entities residing in anygeographic location (e.g., a geographic location 29024 of FIG. 40A). Afourth instruction set may provide a moderation of content about eachother posted of the users 2916 through trusted users of the privacyserver 2900 who have an ability to ban specific users and/or delete anyoffensive and libelous content in the privacy server 2900.

Also, a fifth instruction set may enable an insertion of any contentgenerated in the privacy server 2900 in other search engines through asyndication and/or advertising relationship between the privacy server2900 and/or other internet commerce and search portals.

Moreover, a sixth instruction set may grow the social network throughneighborhood groups, local politicians, block watch communities, issueactivism groups, and neighbor(s) 2920 who invite other known partiesand/or members to share profiles of themselves and/or learncharacteristics and information about other supporters and/or residentsin a geographic area of interest through the privacy server 2900.

Also, a seventh instruction set may determine quantify an effect on atleast one of a desirability of a location, a popularity of a location,and a market value of a location based on an algorithm that considers anumber of demographic and social characteristics of a region surroundingthe location through a reviews module.

FIG. 30 is an exploded view of the social community module 2906 of FIG.29, according to one embodiment. Particularly FIG. 30 illustrates abuilding builder module 3000, an N^(th) degree module 3002, a taggingmodule 3004, a verify module 3006, a groups generator module 3008, apushpin module 3010, a profile module 3012, an announce module 3014, apeople database 3016, a places database 3018, a business database 3020,a friend finder module 3022 and a neighbor-neighbor help module 3024,according to one embodiment.

The N^(th) degree module 3002 may enable the particular registered userto communicate with an unknown registered user through a commonregistered user who may be a friend and/or a member of a commoncommunity. The tagging module 3004 may enable the user 2916 to leavebrief comments on each of the claimable profiles (e.g., the claimableprofile 4006 of FIG. 40A-41B, the claimable profile 4102 of FIG. 41A,the claimable profile 1704 of FIG. 17) and social network pages in theglobal neighborhood environment 1800 (e.g., the privacy server 2900 ofFIG. 29).

The verify module 3006 may validate the data, profiles and/or emailaddresses received from various registered user(s) before any changesmay be included. The groups generator module 3008 may enable theregistered users to form groups may be depending on common interest,culture, style, hobbies and/or caste. The pushpin module 3010 maygenerate customized indicators of different types of users, locations,and interests directly in the map. The profile module 3012 may enablethe user to create a set of profiles of the registered users and tosubmit media content of themselves, identifiable through a map.

The announce module 3014 may distribute a message in a specified rangeof distance away from the registered users when a registered userpurchases a message to communicate to certain ones of the registeredusers surrounding a geographic vicinity adjacent to the particularregistered user originating the message. The people database 3016 maykeep records of the visitor/users (e.g., a user 2916 of FIG. 29). Theplaces database module 3018 may manage the data related to the locationof the user (e.g., address of the registered user). The businessdatabase 3020 may manage an extensive list of leading informationrelated to business. The friend finder module 3022 may match the profileof the registered user with common interest and/or help the registereduser to get in touch with new friends or acquaintances.

For example, the verify module 3006 of the social community module 2906of FIG. 29 may authenticate an email address of a registered user priorto enabling the registered user to edit information associated with theunregistered users through an email response and/or a digital signaturetechnique. The groups generator module 3008 of the social communitymodule (e.g., the social community module 2906 of FIG. 29) may enablethe registered users to form groups with each other surrounding at leastone of a common neighborhood (e.g., a neighborhood 2902A-N of FIG. 29),political, cultural, educational, professional and/or social interest.

In addition, the tagging module 3004 of the social community module(e.g., the social community module 2906 of FIG. 29) may enable theregistered users and/or the unregistered users to leave brief commentson each of the claimable profiles (e.g., the claimable profile 4006 ofFIG. 40A-41B, the claimable profile 4102 of FIG. 41A, the claimableprofile 1704 of FIG. 17) and/or social network pages in the globalneighborhood environment 1800 (e.g., the privacy server 2900 of FIG.29), in which the brief comments may be simultaneously displayed when apointing device rolls over a pushpin indicating a physical propertyassociated with any of the registered users and/or the unregisteredusers. Also, the pushpin module 3010 of the social community module 2906of FIG. 29 may be generating customized indicators of different types ofusers, locations, and/or interests directly in the map.

Further, the announce module 3014 of the social community module 2906 ofFIG. 29 may distribute a message in a specified range of distance awayfrom the registered users when a registered user purchases a message tocommunicate to certain ones of the registered users surrounding ageographic vicinity adjacent to the particular registered useroriginating the message, wherein the particular registered userpurchases the message through a governmental currency and/or a number oftokens collected by the particular user (e.g. the user 2916 of FIG. 29)through a creation of content in the global neighborhood environment1800 (e.g., the privacy server 2900 of FIG. 29).

In addition, the N^(th) degree module 3002 of the social communitymodule 2906 of FIG. 29 may enable the particular registered user tocommunicate with an unknown registered user through a common registereduser known by the particular registered user and/or the unknownregistered user that is an N^(th) degree of separation away from theparticular registered user and/or the unknown registered user.

Moreover, the profile module 3012 of the social community module 2906 ofFIG. 29 may create a set of profiles of each one of the registered usersand to enable each one of the registered users to submit media contentof themselves, other registered users, and unregistered usersidentifiable through the map.

FIG. 31 is an exploded view of the search module 2908 of FIG. 29,according to one embodiment. Particularly FIG. 31 illustrates a peoplesearch widget 3100, a business search module 3102, a category searchwidget 3104, a communication module 3106, a directory assistance module3108, an embedding module 3110, a no-match module 3112, a range selectormodule 3114, a chat widget 3116, a group announcement widget 3118, aVoice Over IP widget 3120, according to one embodiment.

The people search widget 3100 may help in getting the information likethe address, phone number and/or e-mail id of the people of particularinterest from a group and/or community. The business search module 3102may help the users (e.g., the user 2916 of FIG. 29) to find thecompanies, products, services, and/or business related information theyneed to know about.

The category search widget 3104 may narrow down searches from a broaderscope (e.g., if one is interested in information from a particularcenter, one can go to the category under the center and enter one'squery there and it will return results from that particular categoryonly). The communication module 3106 may provide/facilitate multiple bywhich one can communicate, people to communicate with, and subjects tocommunicate about among different members of the global neighborhoodenvironment 1800 (e.g., the privacy server 2900 of FIG. 29).

The directory assistance module 3108 may provide voice responseassistance to users (e.g., the user 2916 of FIG. 29) assessable througha web and telephony interface of any category, business and searchqueries of user's of any search engine contents. The embedding module3110 may automatically extract address and/or contact info from othersocial networks, search engines, and content providers.

The no-match module 3112 may request additional information from averified registered user (e.g., a verified registered user 4110 of FIG.41A-B, a verified registered user 4110 of FIG. 16) about a person,place, and business having no listing in the global neighborhoodenvironment 1800 (e.g., the privacy server 2900 of FIG. 29) when nomatches are found in a search query of the verified registered user(e.g., a verified registered user 4110 of FIG. 41A-B, a verifiedregistered user 4110 of FIG. 16).

The chat widget 3116 may provide people to chat online, which is a wayof communicating by broadcasting messages to people on the same site inreal time. The group announcement widget 3118 may communicate with agroup and/or community in may be by Usenet, Mailing list, calling and/orE-mail message sent to notify subscribers. The Voice over IP widget 3120may help in routing of voice conversations over the Internet and/orthrough any other IP-based network. The communication module 3106 maycommunicate directly with the people search widget 3100, the businesssearch module 3102, the category search widget 3104, the directoryassistance module 3108, the embedding module 3110 may communicate withthe no-match module 3112 through the range selector module 3114.

For example, a search module 2908 of the global neighborhood environment1800 (e.g., the privacy server 2900 of FIG. 29) may enable the peoplesearch, the business search, and the category search of any data in thesocial community module (e.g., the social community module 2906 of FIG.29) and/or may enable embedding of any content in the globalneighborhood environment 1800 (e.g., the privacy server 2900 of FIG. 29)in other search engines, blogs, social networks, professional networksand/or static websites.

In addition, the communicate module 3106 of the search module 2906 mayenable voice over internet, live chat, and/or group announcementfunctionality in the global neighborhood environment 1800 (e.g., theprivacy server 2900 of FIG. 29) among different members of the globalneighborhood environment 1800 (e.g., the privacy server 2900 of FIG.29).

Also, the directory assistance module 3108 of the search module 2908 mayprovide voice response assistance to users (e.g., the user 2916 of FIG.29) assessable through a web and/or telephony interface of any category,business, community, and residence search queries of users (e.g., theuser 2916 of FIG. 29) of any search engine embedding content of theglobal neighborhood environment 1800 (e.g., the privacy server 2900 ofFIG. 29).

The embedding module 3110 of the search module 2908 may automaticallyextract address and/or contact info from other social networks, searchengines, and content providers, and/or to enable automatic extraction ofgroup lists from contact databases of instant messaging platforms.

Furthermore, the no-match module 3112 of the search module 2908 torequest additional information from the verified registered user (e.g.,the verified registered user 4110 of FIG. 41A-B) about a person, place,and/or business having no listing in the global neighborhood environment1800 (e.g., the privacy server 2900 of FIG. 29) when no matches arefound in a search query of the verified registered user (e.g., theverified registered user 4110 of FIG. 41A-B, the verified registereduser 4110 of FIG. 16) and to create a new claimable page based on aresponse of the verified registered user (e.g., the verified registereduser 4110 of FIG. 41A-B, the verified registered user 4110 of FIG. 16)about the at least one person, place, and/or business not previouslyindexed in the global neighborhood environment 1800 (e.g., the privacyserver 2900 of FIG. 29).

FIG. 32 is an exploded view of the claimable module 2910 of FIG. 29,according to one embodiment. Particularly FIG. 32 illustrates auser-place claimable module 3200, a user-user claimable module 3202, auser-neighbor claimable module 3204, a user-business claimable module3206, a reviews module 3208, a defamation prevention module 3210, aclaimable-social network conversion module 3212, a claim module 3214, adata segment module 3216, a dispute resolution module 3218 and a mediamanage module 3220, according to one embodiment.

The user-place claimable module 3200 may manage the information of theuser (e.g., the user 2916 of FIG. 29) location in the globalneighborhood environment 1800 (e.g., the privacy server 2900 of FIG.29). The user-user claimable module 3202 may manage the user (e.g., theuser 2916 of FIG. 29) to view a profile of another user and geographicallocation in the neighborhood. The user-neighbor claimable module 3204may manage the user (e.g., the users 2916 of FIG. 29) to view theprofile of the registered neighbor and/or may trace the geographicallocation of the user in the global neighborhood environment 1800 (e.g.,the privacy server 2900 of FIG. 29). The user-business claimable module3206 may manage the profile of the user (e.g., the user 2916 of FIG. 29)managing a commercial business in the neighborhood environment. Thereviews module 3208 may provide remarks, local reviews and/or ratings ofvarious businesses as contributed by the users (e.g., the user 2916 ofFIG. 29) of the global neighborhood environment 1800 (e.g., the privacyserver 2900 of FIG. 29). The defamation prevention module 3210 mayenable the registered users to modify the information associated withthe unregistered users identifiable through the viewing of the physicalproperties.

The claimable-social network conversion module 3212 of the claimablemodule 2910 of FIG. 29 may transform the claimable profiles (e.g., theclaimable profile 4006 of FIG. 40A-41B, the claimable profile 4102 ofFIG. 41A, the claimable profile 1704 of FIG. 17) to social networkprofiles when the registered users claim the claimable profiles (e.g.,the claimable profile 4006 of FIG. 40A-41B, the claimable profile 4102of FIG. 41A, the claimable profile 1704 of FIG. 17).

The claim module 3214 may enable the unregistered users to claim thephysical properties associated with their residence (e.g., the residence2918 of FIG. 29). The dispute resolution module 3218 may determine alegitimate user among different unregistered users who claim a samephysical property. The media manage module 3220 may allow users (e.g.,the user 2916 of FIG. 29) to manage and/or review a list any productfrom product catalog using a fully integrated, simple to use interface.

The media manage module 3220 may communicate with the user-placeclaimable module 3200, user-place claimable module 3200, user-userclaimable module 3202, the user-neighbor claimable module 3204 and thereviews module 3208 through user-business claimable module 3206. Theuser-place claimable module 3200 may communicate with the disputeresolution module 3218 through the claim module 3214. The user-userclaimable module 3202 may communicate with the data segment module 3216through the claimable-social network conversion module 3212. Theuser-neighbor claimable module 3204 may communicate with the defamationprevention module 3210. The user-business claimable module 3206 maycommunicate with the reviews module 3208. The claimable-social networkconversion module 3212 may communicate with the claim module 3214.

For example, the claimable module 2910 of the global neighborhoodenvironment 1800 (e.g., the privacy server 2900 of FIG. 29) may enablethe registered users to create the social network page of themselves,and may edit information associated with the unregistered usersidentifiable through a viewing of physical properties in which theunregistered users reside when the registered users have knowledge ofcharacteristics associated with the unregistered users. Also, the claimmodule 3214 of claimable module 2910 may enable the unregistered usersto claim the physical properties associated with their residence.

Furthermore, the dispute resolution module 3218 of the claimable module2910 may determine a legitimate user of different unregistered users whoclaim a same physical property. The defamation prevention module 3210 ofthe claimable module 2910 may enable the registered users to modify theinformation associated with the unregistered users identifiable throughthe viewing of the physical properties, and/or to enable registered uservoting of an accuracy of the information associated with theunregistered users.

Moreover, the reviews module of the claimable module 2910 may providecomments, local reviews and/or ratings of various businesses ascontributed by the registered users and/or unregistered users of theglobal network environment (e.g., the privacy server 2900 of FIG. 29).The claimable-social network conversion module 3212 of the claimablemodule 2910 of FIG. 29 may transform the claimable profiles (e.g., theclaimable profile 4006 of FIG. 40A-41B, the claimable profile 4102 ofFIG. 41A, the claimable profile 1704 of FIG. 17) to social networkprofiles when the registered users claim the claimable profiles (e.g.,the claimable profile 4006 of FIG. 40A-41B, the claimable profile 4102of FIG. 41A, the claimable profile 1704 of FIG. 17).

FIG. 33 is an exploded view of the commerce module 2912 of FIG. 29,according to one embodiment. Particularly FIG. 33 illustrates a residentannounce payment module 3300, a business display advertisement module3302, a geo position advertisement ranking module 3304, a contentsyndication module 3306, a text advertisement module 3308, a communitymarketplace module 3310, a click-in tracking module 3312, aclick-through tracking module 3314, according to one embodiment.

The community marketplace module 3310 may contain garage sales 3316, afree stuff 3318, a block party 3320 and a services 3322, according toone embodiment. The geo-position advertisement ranking module 3304 maydetermine an order of the advertisement in a series of otheradvertisements provided in the global neighborhood environment 1800(e.g., the privacy server 2900 of FIG. 29) by other advertisers. Theclick-through tracking module 3314 may determine a number ofclicks-through from the advertisement to a primary website of thebusiness.

A click-in tracking module 3312 may determine a number of user (e.g.,the user 2916 of FIG. 29) who clicked in to the advertisementsimultaneously. The community marketplace module 3310 may provide aforum in which the registered users can trade and/or announce messagesof trading events with at least each other. The content syndicationmodule 3306 may enable any data in the commerce module (e.g., thecommerce module 2912 of FIG. 29) to be syndicated to other network basedtrading platforms.

The business display advertisement module 3302 may impart advertisementsrelated to business (e.g., the business 2922 of FIG. 29), publicrelations, personal selling, and/or sales promotion to promotecommercial goods and services. The text advertisement module 3308 mayenable visibility of showing advertisements in the form of text in alldynamically created pages in the directory. The resident announcepayment module 3300 may take part as component in a broader and complexprocess, like a purchase, a contract, etc.

The block party 3320 may be a large public celebration in which manymembers of a single neighborhood (e.g., the neighborhood 2902A-N of FIG.29) congregate to observe a positive event of some importance. The freestuff 3318 may be the free services (e.g., advertisement, links, etc.)available on the net. The garage sales 3316 may be services that may bedesigned to make the process of advertising and/or may find a garagesale more efficient and effective. The services 3322 may be non-materialequivalent of a good designed to provide a list of services that may beavailable for the user (e.g., the user 2916 of FIG. 29).

The geo position advertisement ranking module 3304 may communicate withthe resident announce payment module 3300, the business displayadvertisement module 3302, the content syndication module 3306, the textadvertisement module 3308, the community marketplace module 3310, theclick-in tracking module 3312 and the click-through tracking module3314.

For example, the commerce module 2908 of the global neighborhoodenvironment 1800 (e.g., the privacy server 2900 of FIG. 29) may providean advertisement system to a business which may purchase their locationin the global neighborhood environment 1800 (e.g., the privacy server2900 of FIG. 29) in which the advertisement may be viewable concurrentlywith a map indicating a location of the business, and/or in whichrevenue may be attributed to the global neighborhood environment 1800(e.g., the privacy server 2900 of FIG. 29) when the registered usersand/or the unregistered users click-in on a simultaneously displayeddata of the advertisement along with the map indicating a location ofthe business.

Also, the geo-position advertisement ranking module 3304 of the commercemodule 2912 to determine an order of the advertisement in a series ofother advertisements provided in the global neighborhood environment1800 (e.g., the privacy server 2900 of FIG. 29) by other advertisers,wherein the advertisement may be a display advertisement, a textadvertisement, and/or an employment recruiting portal associated withthe business that may be simultaneously displayed with the mapindicating the location of the business.

Moreover, the click-through tracking module 3314 of the commerce module2912 of FIG. 29 may determine a number of click-through from theadvertisement to a primary website of the business. In addition, theclick in tracking module 3312 of the commerce module 2912 may determinethe number of users (e.g., the user 2916 of FIG. 29) who clicked in tothe advertisement simultaneously displayed with the map indicating thelocation of the business.

The community marketplace module 3310 of the commerce module 2912 ofFIG. 29 may provide a forum in which the registered users may tradeand/or announce messages of trading events with certain registered usersin geographic proximity from each other.

Also, the content syndication module 3306 of the commerce module 2912 ofthe FIG. 29 may enable any data in the commerce module 2912 to besyndicated to other network based trading platforms.

FIG. 34 is an exploded view of a map module 2914 of FIG. 29, accordingto one embodiment. Particularly FIG. 34 may include a satellite datamodule 3400, a simplified map generator module 3402, a cartoon mapconverter module 3404, a profile pointer module 3406, a parcel module3408 and occupant module 3410, according to one embodiment. Thesatellite data module 3400 may help in mass broadcasting (e.g., maps)and/or as telecommunications relays in the map module 2914 of FIG. 29.

The simplified map generator module 3402 may receive the data (e.g.,maps) from the satellite data module 3400 and/or may convert thiscomplex map into a simplified map with fewer colors. The cartoon mapconverter module 3404 may apply a filter to the satellite data (e.g.,data generated by the satellite data module 3400 of FIG. 34) into asimplified polygon based representation.

The parcel module 3408 may identify some residence, civic, and businesslocations in the satellite data (e.g., the satellite data module 3400 ofFIG. 34). The occupant module 3410 may detect the geographical locationof the registered user in the global neighborhood environment 1800(e.g., the privacy server 2900 of FIG. 29). The profile pointer module3406 may detect the profiles of the registered user via the datareceived from the satellite. The cartoon map converter module 3404 maycommunicate with, the satellite data module 3400, the simplified mapgenerator module 3402, the profile pointer module 3406 and the occupantmodule 3410. The parcel module 3408 may communicate with the satellitedata module 3400.

For example, a map module 2914 of the global neighborhood environment1800 (e.g., the privacy server 2900 of FIG. 29) may include a map dataassociated with a satellite data (e.g., data generated by the satellitedata module 3400 of FIG. 34) which serves as a basis of rendering themap in the global neighborhood environment 1800 (e.g., the privacyserver 2900 of FIG. 29) and/or which includes a simplified map generator(e.g., the simplified map generator module 3402 of FIG. 34) which maytransform the map to a fewer color and location complex form using aparcel data which identifies residence, civic, and business locations inthe satellite data.

Also, the cartoon map converter module 3404 in the map module 2914 mayapply a filter to the satellite data (e.g., data generated by thesatellite data module 3400 of FIG. 34) to transform the satellite datainto a simplified polygon based representation using a Bezier curvealgorithm that converts point data of the satellite data to a simplifiedform.

FIG. 35 is a table view of user address details, according to oneembodiment. Particularly the table 3550 of FIG. 35 illustrates a userfield 3500, a verified? field 3502, a range field 3504, a principleaddress field 3506, a links field 3508, a contributed? field 3510 and anothers field 3512, according to one embodiment. The table 3550 mayinclude the information related to the address verification of the user(e.g., the user 2916 of FIG. 29). The user field 3500 may includeinformation such as the names of the registered users in a globalneighborhood environment 1800 (e.g., a privacy server 2900 of FIG. 29).

The verified? field 3502 may indicate the status whether the data,profiles and/or email address received from various registered user arevalidated or not. The range field 3504 may correspond to the distance ofa particular registered user geographical location in the globalneighborhood environment 1800 (e.g., the privacy server 2900 of FIG.29).

The principal address field 3506 may display primary address of theregistered user in the global neighborhood environment 1800 (e.g., theprivacy server 2900 of FIG. 29). The links field 3508 may further givemore accurate details and/or links of the address of the user (e.g., theuser 2916 of FIG. 29). The contributed? field 3510 may provide the userwith the details of another individual and/or users contribution towardsthe neighborhood environment (e.g., the privacy server 2900 of FIG. 29).The other(s) field 3512 may display the details like the state, city,zip and/or others of the user's location in the global neighborhoodenvironment 1800 (e.g., the privacy server 2900 of FIG. 29).

The user field 3500 displays “Joe” in the first row and “Jane” in thesecond row of the user field 3500 column of the table 3550 illustratedin FIG. 7. The verified field? 3502 displays “Yes” in the first row and“No” in the second row of the verified? field 3502 column of the table3550 illustrated in FIG. 7. The range field 3504 displays “5 miles” inthe first row and “Not enabled” in the second row of the range field3504 column of the table 3550 illustrated in FIG. 7. The principaladdress field 3506 displays “500 Clifford Cupertino, Calif.” in thefirst row and “500 Johnson Cupertino, Calif.” in the second row of theprinciple address field 3506 column of the table 3550 illustrated inFIG. 7. The links field 3508 displays “859 Bette, 854 Bette” in thefirst row and “851 Bette 2900 Steven's Road” in the second row of thelinks field 3508 column of the table 3550 illustrated in FIG. 7.

The contributed? field 3510 displays “858 Bette Cupertino, Calif.,Farallone, Calif.” in the first row and “500 Hamilton, Palo Alto,Calif., 1905E. University” in the second row of the contributed field3510 column of the table 3550 illustrated in FIG. 7. The other(s) field3512 displays “City, State, Zip, other” in the first row of the other(s)field 3512 column of the table 3550 illustrated in FIG. 7.

FIG. 36 is a user interface view of the social community module 2906,according to one embodiment. The user interface view 3650 may displaythe information associated with the social community module (e.g., thesocial community module 2906 of FIG. 29). The user interface 3650 maydisplay map of the specific geographic location associated with the userprofile of the social community module (e.g., the social communitymodule 2906 of FIG. 29). The user interface view 3650 may display themap based geographic location associated with the user profile (e.g.,the user profile 4000 of FIG. 40A) only after verifying the address ofthe registered user of the global neighborhood environment 1800 (e.g.,the privacy server 2900 of FIG. 29).

In addition, the user interface 3650 may provide a building creator(e.g., the building builder 1602 of FIG. 16), in which the registeredusers of the global neighborhood environment 1800 (e.g., the privacyserver 2900 of FIG. 29) may create and/or modify empty claimableprofiles (e.g., a claimable profile 4006 of FIG. 40A-41B, a claimableprofile 4102 of FIG. 41A, a claimable profile 1704 of FIG. 17), buildinglayouts, social network pages, etc. The user interface view 3650 of thesocial community module 2906 may enable access to the user (e.g., theuser 2916 of FIG. 29) to model a condo on any floor (e.g., basement,ground floor, first floor, etc.) selected through the drop down box bythe registered user of the global neighborhood environment 1800 (e.g.,the privacy server 2900 of FIG. 29). The user interface 3650 of thesocial community module (e.g., the social community module 2906 of FIG.29) may enable the registered user of the global neighborhoodenvironment 1800 (e.g., the privacy server 2900 of FIG. 29) tocontribute information about their neighbors (e.g., the neighbor 2920 ofFIG. 29).

FIG. 37 is a profile view 3750 of a profile module 3700, according toone embodiment. The profile view 3750 of profile module 3700 may offerthe registered user to access the profile about the neighbors (e.g., theneighbor 2920 of FIG. 29). The profile view 3750 of profile module 3700may indicate the information associated with the profile of theregistered user of the global neighborhood environment 1800 (e.g., theprivacy server 2900 of FIG. 29). The profile view 3750 may display theaddress of the registered user. The profile view 3750 may also displayevents organized by the neighbors (e.g., the neighbor 2920 of FIG. 29),history of the neighbors (e.g., the neighbor 2920 of FIG. 29), and/ormay also offer the information (e.g., public, private, etc.) associatedwith the family of the neighbors (e.g., the neighbor 2920 of FIG. 29)located in the locality of the user (e.g., the user(s) 2916 of FIG. 29)of the global neighborhood environment 1800 (e.g., the privacy server2900 of FIG. 29).

FIG. 38 is a contribute view 3850 of a neighborhood network module 3800,according to one embodiment. The contribute view 3850 of theneighborhood network module 3800 may enable the registered user of theglobal neighborhood environment 1800 (e.g., the privacy server 2900 ofFIG. 29) to add information about their neighbors in the neighborhoodnetwork. The contribute view 3850 of the neighborhood network module3800 may offer registered user of the global neighborhood environment1800 (e.g., the privacy server 2900 of FIG. 29) to add valuable notesassociated with the family, events, private information, etc.

FIG. 39 is a diagrammatic system view, according to one embodiment. FIG.39 is a diagrammatic system view 3900 of a data processing system 4204in which any of the embodiments disclosed herein may be performed,according to one embodiment. Particularly, the system view 3900 of FIG.39 illustrates a processor 3902, a main memory 3904, a static memory3906, a bus 3908, a video display 3910, an alpha-numeric input device3912, a cursor control device 3914, a drive unit 3916, a signalgeneration device 3918, a network interface device 3920, a machinereadable medium 3922, instructions 3924, and a network 3926, accordingto one embodiment.

The diagrammatic system view 3900 may indicate a personal computerand/or a data processing system 4204 in which one or more operationsdisclosed herein are performed. The processor 3902 may bemicroprocessor, a state machine, an application specific integratedcircuit, a field programmable gate array, etc. (e.g., Intel® Pentium®processor). The main memory 3904 may be a dynamic random access memoryand/or a primary memory of a computer system.

The static memory 3906 may be a hard drive, a flash drive, and/or othermemory information associated with the data processing system 4204. Thebus 3908 may be an interconnection between various circuits and/orstructures of the data processing system 4204. The video display 3910may provide graphical representation of information on the dataprocessing system 4204. The alpha-numeric input device 3912 may be akeypad, keyboard and/or any other input device of text (e.g., a specialdevice to aid the physically handicapped). The cursor control device3914 may be a pointing device such as a mouse.

The drive unit 3916 may be a hard drive, a storage system, and/or otherlonger term storage subsystem. The signal generation device 3918 may bea bios and/or a functional operating system of the data processingsystem 4204. The machine readable medium 3922 may provide instructionson which any of the methods disclosed herein may be performed. Theinstructions 3924 may provide source code and/or data code to theprocessor 3902 to enable any one/or more operations disclosed herein.

FIG. 40A is a user interface view of mapping a user profile 4000 of thegeographic location 4004, according to one embodiment. In the exampleembodiment illustrated in FIG. 40A, the user profile 4000 may containthe information associated with the geographic location 4004. The userprofile 4000 may contain the information associated with the registereduser. The user profile 4000 may contain information such as address userof the specific geographic location, name of the occupant, profession ofthe occupant, details, phone number, educational qualification, etc.

The map 4002 may indicate the global neighborhood environment 1800(e.g., the privacy server 2900 of FIG. 29) of the geographical location4004, a claimable profile 4006 (e.g., the claimable profile 4102 of FIG.41A, the claimable profile 1704 of FIG. 17), and a delisted profile4008. The geographical location 4004 may be associated with the userprofile 4000. The claimable profile 4006 may be the claimable profile4006 associated with the neighboring property surrounding the geographiclocation 4004. The delisted profile 4008 illustrated in exampleembodiment of FIG. 40A, may be the claimable profile 4006 that may bedelisted when the registered user claims the physical property. The tag4010 illustrated in the example embodiment of FIG. 40A may be associatedwith hobbies, personal likes, etc. The block 4016 may be associated withevents, requirements, etc. that may be displayed by the members of theglobal neighborhood environment 1800 (e.g., the privacy server 2900 ofFIG. 29).

For example, a verified registered user (e.g., a verified registereduser 4110 of FIG. 41A-B, a verified registered user 4110 of FIG. 16) maybe associated with a user profile 4000. The user profile 4000 may beassociated with a specific geographic location. A map concurrentlydisplaying the user profile 4000 and the specific geographic location4004 may be generated. Also, the claimable profiles 4006 associated withdifferent geographic locations surrounding the specific geographiclocation associated with the user profile 4000 may be simultaneouslygenerated in the map. In addition, a query of the user profile 4000and/or the specific geographic location may be processed.

Similarly, a tag data (e.g., the tags 4010 of FIG. 40A) associated withthe specific geographic locations, a particular geographic location, andthe delisted geographic location may be processed. A frequent one of thetag data (e.g., the tags 4010 of FIG. 40A) may be displayed when thespecific geographic location and/or the particular geographic locationis made active, but not when a geographic location is delisted.

FIG. 40B is a user interface view of mapping of the claimable profile4006, according to one embodiment. In the example embodiment illustratedin FIG. 40B, the map 4002 may indicate the geographic locations in theglobal neighborhood environment 1800 (e.g., the privacy server 2900 ofFIG. 29) and/or may also indicate the geographic location of theclaimable profile 4006. The claimable profile 4006 may display theinformation associated with the registered user of the globalneighborhood environment 1800 (e.g., the privacy server 2900 of FIG.29). The link claim this profile 4012 may enable the registered user toclaim the claimable profile 4006 and/or may also allow the verifiedregistered user (e.g., the verified registered user 4110 of FIG. 41A-B)to edit any information in the claimable profiles 4006. The block 4014may display the information posted by any of the verified registeredusers (e.g., the verified registered user 4110 of FIG. 41A-B, theverified registered user 4110 of FIG. 16) of the global neighborhoodenvironment 1800 (e.g., the privacy server 2900 of FIG. 29).

For example, a particular claimable profile (e.g., the particularclaimable profile may be associated with a neighboring property to thespecific property in the neighborhood) of the claimable profiles (e.g.,the claimable profile 4102 of FIG. 41A, the claimable profile 1704 ofFIG. 17) may be converted to another user profile (e.g., the userprofile may be tied to a specific property in a neighborhood) when adifferent registered user (e.g., the user 2916 of FIG. 29) claims aparticular geographic location to the specific geographic locationassociated with the particular claimable profile.

In addition, a certain claimable profile of the claimable profiles maybe delisted when a private registered user claims a certain geographiclocation (e.g., the geographical location 4004 of FIG. 40A) adjacent tothe specific geographic location and/or the particular geographiclocation. Also, the certain claimable profile in the map 4002 may bemasked when the certain claimable profile is delisted through therequest of the private registered user.

Furthermore, a tag data (e.g., the tags 4010 of FIG. 40A) associatedwith the specific geographic location, the particular geographiclocation, and the delisted geographic location may be processed. Afrequent one of the tag data may be displayed when the specificgeographic location and/or the particular geographic location are madeactive, but not when a geographic location is delisted.

Moreover, the verified registered user (e.g., the verified registereduser 4110 of FIG. 41A-B, the verified registered user 4110 of FIG. 16)may be permitted to edit any information in the claimable profiles 4006including the particular claimable profile 4006 and/or the certainclaimable profile until the certain claimable profile may be claimed bythe different registered user and/or the private registered user. Inaddition, a claimant of any claimable profile 4006 may be enabled tocontrol what information is displayed on their user profile. Also, theclaimant may be allowed to segregate certain information on their userprofile 4000 such that only other registered users directly connected tothe claimant are able to view data on their user profile 4000.

FIG. 41A is a user interface view of mapping of a claimable profile 4102of the commercial user 4100, according to one embodiment. In the exampleembodiment illustrated in FIG. 41A, the commercial user 4100 may beassociated with the customizable business profile 4104 located in thecommercial geographical location. The claimable profile 4102 may containthe information associated with the commercial user 4100. The claimableprofile 4102 may contain the information such as address, name,profession, tag, details (e.g., ratings), and educational qualificationetc. of the commercial user 4100. The verified registered user 4110 maybe user associated with the global neighborhood environment 1800 (e.g.,the privacy server 2900 of FIG. 29) and may communicate a message to theneighborhood commercial user 4100. For example, a payment of thecommercial user 4100 and the verified registered user 4110 may beprocessed.

FIG. 41B is a user interface view of mapping of customizable businessprofile 4104 of the commercial user 4100, according to one embodiment.In the example embodiment illustrated in FIG. 41B, the commercial user4100 may be associated with the customizable business profile 4104. Thecustomizable business profile 4104 may be profile of any business firm(e.g., restaurant, hotels, supermarket, etc.) that may containinformation such as address, occupant name, profession of thecustomizable business. The customizable business profile 4104 may alsoenable the verified registered user 4110 to place online order for theproducts.

For example, the commercial user 4100 may be permitted to purchase acustomizable business profile 4104 associated with a commercialgeographic location. Also, the verified registered user 4110 may beenabled to communicate a message to the global neighborhood environment1800 (e.g., the privacy server 2900 of FIG. 29) based on a selectabledistance range away from the specific geographic location. In addition,a payment of the commercial user 4100 and/or the verified registereduser 4110 may be processed.

A target advertisement 4106 may display the information associated withthe offers and/or events of the customizable business. The displayadvertisement 4108 may display ads of the products of the customizablebusiness that may be displayed to urge the verified registered user 4110to buy the products of the customizable business. The verifiedregistered user 4110 may be user associated with the global neighborhoodenvironment 1800 (e.g., the privacy server 2900 of FIG. 29) that maycommunicate a message to the commercial user 4100 and/or may beinterested in buying the products of the customizable business.

FIG. 42 is a network view of a commerce server having a radialdistribution module communicating with a data processing system thatgenerates a radial broadcast through an internet protocol network usinga radial algorithm of the radial distribution module of the commerceserver, according to one embodiment.

Particularly, FIG. 42 illustrates a view of the community network view4250, according to one embodiment. The embodiment of FIG. 42 describes acommerce server 4200, the network 2904, a broadcast data 4202, a set ofgeospatial coordinates 4203, a data processing system 4204 (e.g., asmart phone, a tablet, a laptop, a computer, and/or a personalelectronic device), the user 2916, a cellular network 2908, serviceproviders 4209 (including a repair service provider, an emergencyresponse provider (e.g., a police station, a fire station, anambulance), a retail establishment, a restaurant, a grocery store), anotification data 4212, a set of recipients 4214, an area outside thethreshold radial distance 4215, a geospatial area 4217, a thresholdradial distance 4219, a processor 4220, a geospatial database 4222, amemory 4224, a radial distribution module 4240 (e.g., that applies aradial algorithm 4241 of FIG. 2 using a series of modules working inconcert as described in FIG. 2), a geospatially constrained socialnetwork 4242, an epicenter 4244, a massively parallel computingarchitecture 4246, the autonomous neighborhood multi-copter 100, adistributed computing system 4248, a heartbeat message 4260, a currentgeo-spatial coordinates of the autonomous neighborhood multi-copter4262, a time stamp 4264, a date stamp 4266, and an operational status ofthe vehicle 4268.

The commerce server 4200 includes a processor 4220, a memory 4224, and ageospatial database 4222, according to the embodiment of FIG. 42. Thecommerce server 4200 may be one or more server side data processingsystems (e.g., web servers operating in concert with each other) thatoperate in a manner that provide a set of instructions to any number ofclient side devices (e.g., the data processing system 4204 (e.g., asmart phone, a laptop, a tablet, a computer) communicatively coupledwith the commerce server 4200 through the network 2904. For example, thecommerce server 4200 may be a computing system (e.g., or a group ofcomputing systems) that operates in a larger client-server databaseframework (e.g., such as in a social networking software such asNextdoor.com, Fatdoor.com, Facebook.com, etc.).

The data processing system 4204 (e.g., a smartphone, a tablet, a laptop)may access the commerce server 4200 through the network 2904 using abrowser application of the data processing system (e.g., Google® Chrome)and/or through a client-side application downloaded to the dataprocessing system 4204 (e.g., a Nextdoor.com mobile application, aFatdoor.com mobile application) operated by the user 2916. In analternate embodiment, a non-mobile computing device, such as a desktopcomputer (not shown) may access the commerce server 4200 through thenetwork 2904.

The broadcast data 4202 may be communicated from the data processingsystem 4204 to the commerce server 4200 through the network 2904. Thebroadcast data 4202 may include information about a garage sale offeredby the user 2916 to recipients 4214 through the network 2904. Forexample, the work opportunity may relate to a paid position of regularemployment offered by the user 2916 and/or a task, a casual/occasionalgarage sale offered by the user 2916 to the recipients 4214 and/or theservice providers 4209.

The broadcast data 4202 may be generated and distributed through anapplication of the radial distribution module 4240 (e.g., that appliesthe radial algorithm 4241 using a series of modules working in concert)of the commerce server 4200. The radial distribution module 4240 (e.g.,that applies the radial algorithm 4241 using a series of modules workingin concert) may be a series of software functions/processes thatsimulates the experience of transmitting and receiving local broadcastsfor the verified user (e.g., the user 2916 that has claimed a geospatiallocation), according to one embodiment.

Using an internet protocol based network (e.g., the network 2904), thecommerce server 4200 may be able to use the radial distribution module4240 (e.g., that applies the radial algorithm 4241 using a series ofmodules working in concert) to simulate a radio frequency (RF) basedcommunication network using an IP network topology of the network 2904.Therefore, the broadcast data 4202 can be distributed using the commerceserver 4200 to a geo-constrained area (e.g., the recipients 4214 in thegeospatial area 4217 and/or the service providers 4209 in ageo-constrained area around an area in which the data processing system4204 operates without requiring expensive broadcast towers,transceivers, transmitters, amplifiers, antennas, tuners and/or wavegenerating and interpreting hardware (e.g., as may be required in localham radio communication, frequency modulation (FM) audio systems, etc.).The radial distribution module 4240 (e.g., that applies the radialalgorithm 4241 using a series of modules working in concert) mayrecreate an experience of communication between parties in ageospatially restricted area (e.g., for example in the same city, in thesurrounding neighborhood, in the same zip code, in the same building, inthe same claimed neighborhood) through the use of an Internet protocolnetwork. The commerce server 4200 may overcome technical challenges ofdetermining a user's geospatial location, calculating distance to otherverified users based on relative geospatial locations, and/orcoordinating information with a database of geo-coded information ofinterest (e.g., using the geospatial database 4222) using the radialdistribution module 4240 (e.g., that applies the radial algorithm 4241using a series of modules working in concert).

The radial distribution module 4240 (e.g., that applies the radialalgorithm 4241 using a series of modules working in concert), as afunction/module of the commerce server, may determine the location ofthe user 2916, the distance between the user 2916 and other verifiedusers, and the distance between the user 2916 and locations of interest.With that information, the radial distribution module 4240 (e.g., thatapplies the radial algorithm 4241 using a series of modules working inconcert) may further determine which verified users are within apredetermined vicinity of a user 2916. This set of verified users withinthe vicinity of another verified user may then be determined to bereceptive to broadcasts transmitted by the user 2916 and to be availableas transmitters of broadcasts to the user 2916.

The radial distribution module 4240 (e.g., that applies the radialalgorithm 4241 using a series of modules working in concert) in effectmay create a link between verified users of the network 2904 that allowsthe users to communicate with each other, and this link may be based onthe physical distance between the users as measured relative to acurrent geospatial location of the data processing system 4204 with aclaimed and verified (e.g., through a verification mechanism such as apostcard verification, a utility bill verification, and/or a vouching ofthe user with other users) non-transitory location (e.g., a homelocation, a work location) of the user and/or other users. In analternate embodiment, the transitory location of the user (e.g., theircurrent location, a current location of their vehicle and/or mobilephone) and/or the other users may also be used by the radial algorithm4241 to determine an appropriate threshold distance for broadcasting amessage.

Furthermore, the radial distribution module 4240 (e.g., that applies theradial algorithm 4241 using a series of modules working in concert) mayautomatically update a set of pages associated with profiles ofindividuals and/or businesses that have not yet joined the network basedon preseeded address information. In effect, the radial distributionmodule 4240 (e.g., that applies the radial algorithm 4241 using a seriesof modules working in concert) may update preseeded pages in ageo-constrained radial distance from where a broadcast originates (e.g.,using an epicenter 4244 calculated from the current location of the dataprocessing system 4204) with information about the broadcast data 4202.In effect, through this methodology, the radial distribution module 4240(e.g., that applies the radial algorithm 4241 using a series of modulesworking in concert) may leave ‘inboxes’ and/or post ‘alerts’ on pagescreated for users that have not yet signed up based on a confirmedaddress of the users through a public and/or a private data source(e.g., from Infogroup®, from a white page directory, etc.).

The radial distribution module 4240 (e.g., that applies the radialalgorithm 4241 using a series of modules working in concert) of thecommerce server 4200 may be different from previous implementationsbecause it is the first implementation to simulate the experience oflocal radio transmission between individuals using the internet andnon-radio network technology by basing their network broadcast range onthe proximity of verified users to one another, according to oneembodiment.

FIG. 42 illustrates a number of operations between the data processingsystem 4204 and the recipients 4214 and/or the service providers 4209.Particularly, circle ‘ 1’ of FIG. 42 illustrates that the user of thedata processing system 4204 communicates the broadcast data 4202 to thecommerce server 4200 using the network 2904. Then, after applying theradial algorithm 4241 utilizing the radial distribution module 4240, thecommerce server 4200 generates and communicates an appropriatenotification data (e.g., the notification data 4212) associated with thebroadcast data 4202 to a geospatially distributed set of recipients 4214in a radial area (radius represented as ‘r’ of FIG. 42) in a geospatialvicinity from an epicenter 4244 associated a present geospatial locationwith the data processing system 4204 as illustrated as circle ‘2’ inFIG. 42.

The radial algorithm 4241 may operate as follows, according to oneembodiment. The radial algorithm may utilize a radial distributionfunction (e.g., a pair correlation function)g(r)

in the view of the community network 4250. The radial distributionfunction may describe how density varies as a function of distance froma user 2916, according to one embodiment.

If a given user 2916 is taken to be at the origin O (e.g., the epicenter4244), and ifρ=N/Vis the average number density of recipients 4214 in the view of thecommunity network view 4250, then the local time-averaged density at adistance r from O isρg(r)according to one embodiment. This simplified definition may hold for ahomogeneous and isotropic type of recipients 4214, according to oneembodiment of the radial algorithm 4241.

A more anisotropic distribution (e.g., exhibiting properties withdifferent values when measured in different directions) of therecipients 4214 will be described below, according to one embodiment ofthe radial algorithm 4241. In simplest terms it may be a measure of theprobability of finding a recipient at a distance of r away from a givenuser 2916, relative to that for an ideal distribution scenario,according to one embodiment. The anisotropic algorithm involvesdetermining how many recipients 4214 are within a distance of r and r+draway from the user 2916, according to one embodiment. The radialalgorithm 4241 may be determined by calculating the distance between alluser pairs and binning them into a user histogram, according to oneembodiment.

The histogram may then be normalized with respect to an ideal user atthe origin o, where user histograms are completely uncorrelated,according to one embodiment. For three dimensions (e.g., such as abuilding representation in the geospatially constrained social network4242 in which there are multiple residents in each floor), thisnormalization may be the number density of the system multiplied by thevolume of the spherical shell, which mathematically can be expressed asg(r)_(I)=4πr ² ρdr,where ρ may be the user density, according to one embodiment of theradial algorithm 4241.

The radial distribution function of the radial algorithm 4241 can becomputed either via computer simulation methods like the Monte Carlomethod, or via the Ornstein-Zernike equation, using approximate closurerelations like the Percus-Yevick approximation or the Hypernetted ChainTheory, according to one embodiment

This may be important because by confining the broadcast reach of averified user in the view of the community network view 4250 to aspecified range, the radial distribution module 4240 (e.g., that appliesthe radial algorithm 4241 using a series of modules working in concert)may replicate the experience of local radio broadcasting and enableverified users to communicate information to their immediate neighborsas well as receive information from their immediate neighbors in areasthat they care about, according to one embodiment. Such methodologiescan be complemented with hyperlocal advertising targeted to potentialusers of the commerce server 4200 on preseeded profile pages and/oractive user pages of the commerce server 4200. Advertisementcommunications thus may become highly specialized and localizedresulting in an increase in their value and interest to the localverified users of the network through the commerce server 4200.

The radial distribution module 4240 (e.g., that applies the radialalgorithm 4241 using a series of modules working in concert) may solvethe problem of trying to locate a receptive audience to a verifieduser's broadcasts, whether that broadcast may be one's personal music,an advertisement for a car for sale, a solicitation for a new employee,and/or a recommendation for a good restaurant in the area. This radialdistribution module 4240 (e.g., that applies the radial algorithm 4241using a series of modules working in concert) may eliminateunnecessarily broadcasting that information to those who are notreceptive to it, both as a transmitter and as a recipient of thebroadcast. The radial algorithm 4241 saves both time and effort of everyuser involved by transmitting information only to areas that a usercares about, according to one embodiment.

In effect, the radial algorithm 4241 of the commerce server 4200 enablesusers to notify people around locations that are cared about (e.g.,around where they live, work, and/or where they are physically located).In one embodiment, the user 2916 can be provided ‘feedback’ after thebroadcast data 4202 may be delivered to the recipients 4214 and/or tothe service providers 4209 using the radial distribution module 4240(e.g., that applies the radial algorithm 4241 using a series of modulesworking in concert) of the commerce server 4200. For example, after thebroadcast data 4202 may be delivered, the data processing system 4204(e.g., a data processing system 504) may display a message saying: “3256neighbors around a 1 mile radius from you have been notified on theirprofile pages of your delivery notification in Menlo Park” and/or “8356neighbors around a 1 mile radius from you have been notified of yourrequest to rent an autonomous neighborhood multi-copter.”

The various embodiments described herein of the commerce server 4200using the radial distribution module 4240 (e.g., that applies the radialalgorithm 4241 using a series of modules working in concert) may solve acentral problem of internet radio service providers (e.g., Pandora) byretaining cultural significance related to a person's locations ofassociation. For example, the radial distribution module 4240 (e.g.,that applies the radial algorithm 4241 using a series of modules workingin concert) may be used to ‘create’ new radio stations, televisionstations, and/or mini alert broadcasts to a geospatially constrainedarea on one end, and provide a means for those ‘tuning in’ to consumeinformation posted in a geospatial area that the listener cares aboutand/or associates themselves with. The information provided can beactionable in that the user 2916 may be able to secure new opportunitiesthrough face to face human interaction and physical meeting nototherwise possible in internet radio scenarios.

The radial algorithm 4241 may be a set of instructions that may enableusers (e.g., verified users, non-verified users) of the Nextdoor.com andFatdoor.com websites and applications to broadcast their activities(e.g., deliveries, pick-ups, errands, garage sale, t-shirt sale, crimealert) to surrounding neighbors within a claimed neighborhood and toguests of a claimed neighborhood, according to one embodiment. Theradial algorithm 4241 may be new because current technology does notallow for users of a network (e.g., Nextdoor.com, Fatdoor.com) tolocally broadcast their activity to a locally defined geospatial area.With the radial algorithm 4241, users of the network may communicatewith one another in a locally defined manner, which may present morerelevant information and activities, according to one embodiment. Forexample, if a verified user of the network broadcasts a task for theautonomous neighborhood multi-copter, locally defined neighbors of theverified user may be much more interested in the tasks and needs ofindividuals in their neighborhood compared to if the task was forsomeone or something in a different town or city, according to oneembodiment. The radial distribution module 4240 may solve the problem ofneighbors living in the locally defined geospatial area who don'ttypically interact, and allows them to connect within a virtual spacethat did not exist before, according to one embodiment. Prior to thisinvention of the radial algorithm 4241 operating through the radialdistribution module 4240, community boards (e.g., job boards, for saleboards) were the only method of distributing content in a surroundingneighborhood effectively. However, there was no way to easily distributecontent related to exigent circumstances and/or with urgency in abroadcast-like manner to those listening around a neighborhood throughdata processing systems until the various embodiments applying theradial distribution module 4240 as described herein.

A radial algorithm 4241 may be a method of calculating a sequence ofoperations, and in this case a sequence of radio operations, accordingto one embodiment. Starting from an initial state and initial input, theradial algorithm 4241 describes a computation that, when executed,proceeds through a finite number of well-defined successive states,eventually producing radial patterned distribution (e.g., simulating alocal radio station), according to one embodiment.

The commerce server 4200 may solve technical challenges through theradial distribution module 4240 (e.g., that applies the radial algorithm4241 using a series of modules working in concert) by implementing avigorous screening process to screen out any lewd or vulgar content inone embodiment. For example, what may be considered lewd contentsometimes could be subjective, and verified users could argue that weare restricting their constitutional right to freedom of speech througha crowd-moderation capability enabled by the radial distribution module4240 (e.g., that applies the radial algorithm 4241 using a series ofmodules working in concert), according to one embodiment. In oneembodiment, verified users may sign an electronic agreement to screentheir content and agree that the view of the community network view 4250may delete any content that it deems inappropriate for broadcasting,through the radial distribution module 4240 (e.g., that applies theradial algorithm 4241 using a series of modules working in concert)according to one embodiment.

The radial distribution module 4240 (e.g., that applies the radialalgorithm 4241 using a series of modules working in concert) may allowverified users to create and broadcast their own radio show, e.g.,music, talk show, commercial, instructional contents, etc., and tochoose their neighborhood(s) for broadcasting based on a claimedlocation, according to one embodiment. The radial distribution module4240 (e.g., that applies the radial algorithm 4241 using a series ofmodules working in concert) may allow users to choose the neighborhoodsthat they would want to receive the broadcasts, live and recordedbroadcasts, and/or the types and topics of broadcasts that interestthem.

The radial distribution module 4240 (e.g., that applies the radialalgorithm 4241 using a series of modules working in concert) basedapproach of the commerce server 4200 may be a completely differentconcept from the currently existing neighborhood (e.g. geospatial)social networking options. The radial distribution module 4240 (e.g.,that applies the radial algorithm 4241 using a series of modules workingin concert) may also allow the user to create his/her own radio station,television station and/or other content such as the broadcast data 4202and distribute this content around locations to users and preseededprofiles around them. The radial distribution module 4240 (e.g., thatapplies the radial algorithm 4241 using a series of modules working inconcert) can allow verified users to create their content and broadcastin the selected geospatial area. It also allows verified listeners tolisten to only the relevant local broadcasts of their choice.

The radial distribution module 4240 (e.g., that applies the radialalgorithm 4241 using a series of modules working in concert) may beimportant because it may provide any verified user the opportunity tocreate his/her own radial broadcast message (e.g., can be audio, video,pictorial and/or textual content) and distribute this content to a broadgroup. Radial distribution module 4240 (e.g., that applies the radialalgorithm 4241 using a series of modules working in concert) may alsoallow verified listeners to listen to any missed live broadcasts throughthe prerecorded features, according to one embodiment. Through this, theradial distribution module 4240 (e.g., that applies the radial algorithm4241 using a series of modules working in concert) changes the waysocial networks (e.g., Nextdoor, Fatdoor, Facebook, Path, etc.) operateby enabling location centric broadcasting to regions that a user caresabout, according to one embodiment. Radial distribution module 4240(e.g., that applies the radial algorithm 4241 using a series of modulesworking in concert) may solve a technical challenge by defining rangesbased on a type of job posting, a type of neighborhood, and/or boundarycondition of a neighborhood by analyzing whether the broadcast data 4202may be associated with a particular kind of job, a particularneighborhood, a temporal limitation, and/or through another criteria.

By using the radial distribution module 4240 (e.g., that applies theradial algorithm 4241 using a series of modules working in concert) ofthe commerce server 4200 the verified user 2916 may be able to filterirrelevant offers and information provided by broadcasts. In oneembodiment, only the broadcasting user (e.g., the user 2916) may be averified user to create accountability for a particular broadcast and/orcredibility of the broadcaster. In this embodiment, recipients 4214 ofthe broadcast may not need to be verified users of the garage salenetwork. By directing traffic and organizing the onslaught ofbroadcasts, the radial distribution module 4240 (e.g., that applies theradial algorithm 4241 using a series of modules working in concert) ofthe commerce server 4200 may able to identify the origins and nature ofeach group of incoming information and locate recipients 4214 that arerelevant/interested in the broadcast data 4202, maximizing the effectiveuse of each broadcast.

The radial distribution module 4240 (e.g., that applies the radialalgorithm 4241 using a series of modules working in concert) of thecommerce server 4200 may process the input data from the data processingsystem 4204 in order to identify which notification(s) to broadcast towhich individual(s). This may be separate from a traditional radiobroadcast as it not only geographically constrains broadcasters andrecipients 4214 but also makes use of user preferences in order to allowbroadcasters to target an optimal audience and allow recipients 4214 toalter and customize what they consume. The user 2916 may associatehimself/herself with a non-transitory address in order to remainconstantly connected to their neighborhood and/or neighbors even whenthey themselves or their neighbors are away. The radial algorithm 4241may be also unique from a neighborhood social network (e.g., thegeospatially constrained social network 4242) as it permits users tobroadcast offers, information, audio, video etc. to other users,allowing users to create their own stations.

In order to implement the radial distribution module 4240 (e.g., thatapplies the radial algorithm 4241 using a series of modules working inconcert), geospatial data may need to be collected and amassed in orderto create a foundation on which users may sign up and verify themselvesby claiming a specific address, associating themselves with thatgeospatial location. The radial distribution module 4240 (e.g., thatapplies the radial algorithm 4241 using a series of modules working inconcert) may then be able to utilize the geospatial database 4222 tofilter out surrounding noise and deliver only relevant data torecipients 4214. In order to accomplish this, the radial distributionmodule 4240 (e.g., that applies the radial algorithm 4241 using a seriesof modules working in concert) may be able to verify the reliability ofgeospatial coordinates, time stamps, and user information associatedwith the data processing system 4204 (e.g., a data processing system504). In addition, threshold geospatial radii, private neighborhoodboundaries, and personal preferences may be established in the commerceserver 4200 and accommodated using the radial distribution module 4240(e.g., that applies the radial algorithm 4241 using a series of modulesworking in concert). The geospatial database 4222 may work in concertwith the radial distribution module 4240 (e.g., that applies the radialalgorithm 4241 using a series of modules working in concert) to store,organize, and manage broadcasts, pushpins, user profiles, preseeded userprofiles, metadata, and epicenter 4244 locations associated with thegeospatially constrained social network 4242 (e.g., a neighborhoodsocial network such as Fatdoor.com, Nextdoor.com).

The radial algorithm 4241 may be used to calculate relative distancesbetween each one of millions of records as associated with each placedgeo-spatial coordinate in the geospatially constrained social network4242 (e.g., a neighborhood social network such as Fatdoor.com,Nextdoor.com). Calculations of relative distance between each geospatialcoordinate can be a large computational challenge because of the highnumber of reads, writes, modifies, and creates associated with eachgeospatial coordinate added to the geospatially constrained socialnetwork 4242 and subsequent recalculations of surrounding geospatialcoordinates associated with other users and/or other profile pages baseda relative distance away from a newly added set of geospatialcoordinates (e.g., associated with the broadcast data 4202 and/or withother pushpin types). To overcome this computational challenge, theradial algorithm may leverage a massively parallel computingarchitecture 4246 through which processing functions are distributedacross a large set of processors accessed in a distributed computingsystem 4248 through the network 2904.

In order to achieve the utilization of the massively parallel computingarchitecture 4246 in a context of a radial distribution function of ageospatially constrained social network 4242, a number of technicalchallenges have been overcome in at least one embodiment. Particularly,the radial distribution module 4240 constructs a series of tables basedon an ordered geospatial ranking based on frequency of interactionthrough a set of ‘n’ number of users simultaneously interacting with thegeospatially constrained social network 4242, in one preferredembodiment. In this manner, sessions of access between the commerceserver 4200 and users of the commerce server 4200 (e.g., the user 2916)may be monitored based on geospatial claimed areas of the user (e.g., aclaimed work and/or home location of the user), and/or a presentgeospatial location of the user. In this manner, tables associated withdata related to claimed geospatial areas of the user and/or the presentgeospatial location of the user may be anticipatorily cached in thememory 4224 to ensure that a response time of the geospatiallyconstrained social network 4242 may be not constrained by delays causedby extraction, retrieval, and transformation of tables that are notlikely to be required for a current and/or anticipated set of sessionsbetween users and the commerce server 4200.

In a preferred embodiment, an elastic computing environment may be usedby the radial distribution module 4240 to provide for increase/decreasesof capacity within minutes of a database function requirement. In thismanner, the radial distribution module 4240 can adapt to workloadchanges based on number of requests of processing simultaneous and/orconcurrent requests associated with broadcast data 4202 by provisioningand deprovisioning resources in an autonomic manner, such that at eachpoint in time the available resources match the current demand asclosely as possible.

The radial distribution module 4240 (e.g., that applies the radialalgorithm 4241 using a series of modules working in concert) may be aconcept whereby a server communicating data to a dispersed group ofrecipients 4214 over a network 2904, which may be an internet protocolbased wide area network (as opposed to a network communicating by radiofrequency communications) communicates that data only to ageospatially-constrained group of recipients 4214. The radialdistribution module 4240 (e.g., that applies the radial algorithm 4241using a series of modules working in concert) may apply a geospatialconstraint related to a radial distance away from an origin point, or aconstraint related to regional, state, territory, county, municipal,neighborhood, building, community, district, locality, and/or othergeospatial boundaries.

The radial distribution module 4240 (e.g., that applies the radialalgorithm 4241 using a series of modules working in concert) may be newas applied to data traveling over wide area networks using internetprotocol topology in a geospatial social networking and commercecontext, according to one embodiment. While radio broadcasts, by theirnature, are transmitted in a radial pattern surrounding the originpoint, there may be no known mechanism for restricting access to thedata only to verified users of a service subscribing to the broadcast.As applied to wired computer networks, while techniques for applyinggeospatial constraints have been applied to search results, and to otherlimited uses, there has as yet been no application of geospatialconstraint as applied to the various embodiments described herein usingthe radial distribution module 4240 (e.g., that applies the radialalgorithm 4241 using a series of modules working in concert).

The radial distribution module 4240 (e.g., that applies the radialalgorithm 4241 using a series of modules working in concert) may beroughly analogous to broadcast radio communications such as a) inbroadcast radio, b) in wireless computer networking, and c) in mobiletelephony. However, all of these systems broadcast their informationpromiscuously, making the data transmitted available to anyone withinrange of the transmitter who may be equipped with the appropriatereceiving device. In contrast, the radial distribution module 4240(e.g., that applies the radial algorithm 4241 using a series of modulesworking in concert) herein describes a system in which networks are usedto transmit data in a selective manner in that information may bedistributed around a physical location of homes or businesses in areasof interest/relevancy.

The radial distribution module 4240 (e.g., that applies the radialalgorithm 4241 using a series of modules working in concert) may solve aproblem of restricting data transmitted over networks to specific userswho are within a specified distance from the individual who originatesthe data. In a broad sense, by enabling commerce and communications thatare strictly limited within defined neighborhood boundaries, the radialdistribution module 4240 (e.g., that applies the radial algorithm 4241using a series of modules working in concert) may enable thegeospatially constrained social network 4242 (e.g., a neighborhoodsocial network such as Fatdoor.com, Nextdoor.com) communications,attacking the serious social conditions of anonymity and disengagementin community that afflict the nation and, increasingly, the world.

The radial distribution module 4240 (e.g., that applies the radialalgorithm 4241 using a series of modules working in concert) maycomprise one or more modules that instruct the commerce server 4200 torestrict the broadcasting of the broadcast data 4202 to one or moreparts of the geospatial area 4217. For example, in the embodiment ofFIG. 42, the radial distribution module 4240 (e.g., that applies theradial algorithm 4241 using a series of modules working in concert) mayinstruct the commerce server 4200 to broadcast the broadcast data 4202to the recipients 4214 but not to the area outside the threshold radialdistance 4215.

In one or more embodiments, the radial distribution module 4240 (e.g.,that applies the radial algorithm 4241 using a series of modules workingin concert) may allow the commerce server 4200 to function in mannerthat simulates a traditional radio broadcast (e.g., using a radio towerto transmit a radio frequency signal) in that both the commerce server4200 and the radio broadcast are restricted in the geospatial scope ofthe broadcast transmission. In one or more embodiments, the radialdistribution module 4240 (e.g., that applies the radial algorithm 4241using a series of modules working in concert) may prevent the broadcastof the broadcast data 4202 to any geospatial area to which the user 2916does not wish to transmit the broadcast data 4202, and/or to users thathave either muted and/or selectively subscribed to a set of broadcastfeeds.

The radial distribution module 4240 (e.g., that applies the radialalgorithm 4241 using a series of modules working in concert) may analyzethe broadcast data 4202 to determine which recipients 4214 may receivenotification data 4212 within a threshold radial distance 4219 (e.g.,set by the user 2916 and/or auto calculated based on a type ofbroadcast). The radial distribution module 4240 (e.g., that applies theradial algorithm 4241 using a series of modules working in concert) mayuse a variety of parameters, including information associated with thebroadcast data to determine the threshold radial distance 4219.

The radial distribution module 4240 (e.g., that applies the radialalgorithm 4241 using a series of modules working in concert) may alsodetermine which verified addresses associated with recipients 4214having verified user profiles are located within the threshold radialdistance 4219. The radial distribution module 4240 (e.g., that appliesthe radial algorithm 4241 using a series of modules working in concert)may then broadcast the notification data 4212 to the profiles and/ordata processing systems of the verified users having verified addresseswithin the threshold radial distance 4219.

The radial distribution module 4240 (e.g., that applies the radialalgorithm 4241 using a series of modules working in concert) maytherefore simulate traditional radio broadcasting (e.g. from a radiostation transmission tower) over the IP network. Thus, the radialdistribution module 4240 (e.g., that applies the radial algorithm 4241using a series of modules working in concert) may allow the broadcast toinclude information and data that traditional radio broadcasts may notbe able to convey, for example geospatial coordinates and/or real-timebi-directional communications. Additionally, the radial distributionmodule 4240 (e.g., that applies the radial algorithm 4241 using a seriesof modules working in concert) may allow individual users low-entrybroadcast capability without resort to expensive equipment and/orlicensing by the Federal Communications Commission (FCC).

Another advantage of this broadcast via the radial distribution module4240 (e.g., that applies the radial algorithm 4241 using a series ofmodules working in concert) may be that it may bypass obstructions thattraditionally disrupt radio waves such as mountains and/or atmosphericdisturbances. Yet another advantage of the radial distribution module4240 (e.g., that applies the radial algorithm 4241 using a series ofmodules working in concert) may be that it may expand the physicaldistance of broadcast capability without resort to the expenseordinarily associated with generating powerful carrier signals. In yetanother advantage, the radial distribution module 4240 (e.g., thatapplies the radial algorithm 4241 using a series of modules working inconcert) may allow for almost unlimited channels and/or stations ascompared to traditional radio where only a narrow band ofelectromagnetic radiation has been appropriated for use among a smallnumber of entities by government regulators (e.g. the FCC).

The user 2916 may be an individual who operates the data processingsystem 4204 (e.g., a data processing system 504) to generate thebroadcast data 4202. It will be understood by those skilled in the artthat the verified nature of the user may be an optional characteristicin an alternate embodiment. This means that in an alternate embodiment,any user (whether verified or not) may generate the broadcast data 4202through the data processing system 4204. In another alternativeembodiment, the user 2916 may be an electronic sensor, such as adetection sensor device (e.g., a sensory detection sensor device such asa motion detector, a chemical detection device, etc.), and/or anappliance (e.g., such as a refrigerator, a home security network, and/ora motion detector). It should also be noted that the ‘mobile’ nature ofthe data processing system 4204 may be optional in yet anotheralternative embodiment. In such an alternate embodiment, any computingdevice, whether mobile/portable or fixed in location may generate thebroadcast data 4202.

The cellular network 2908 may be associated with a telephone carrier(e.g., such as AT&T, Sprint, etc.) that provides an infrastructurethrough which communications are generated between the commerce server4200 and the service providers 4209 using the radial algorithm 4241. Forexample, the cellular network 2908 may provide a communicationinfrastructure through which the broadcast data 4202 may be communicatedas voice and/or text messages through telephones (e.g., standardtelephones and/or smart phones) operated by at least some of the serviceproviders 4209 of FIG. 42. It should be understood that in oneembodiment, the service providers 4209 are paid subscribers/customers ofthe geospatially constrained social network 4242 in a manner such thateach of the service providers 4209 may pay a fee per received broadcastdata 4202, and/or each hired engagement to the geospatially constrainedsocial network 4242. The service providers 4209 may pay extra to bepermitted access to receive the broadcast data 4202 even when they donot have a transitory and/or non-transitory connection to a neighborhoodif they service that neighborhood area though operating their businessoutside of it. For this reason, FIG. 42 visually illustrates that theservice providers 4209 may be located (e.g., principal business address)outside the threshold radial distance 4219.

The cellular network 2908 (e.g., a mobile network) may be a wirelessnetwork distributed over land areas called cells, each served by atleast one fixed-location transceiver, known as a cell site or basestation through which the broadcast data 4202 is distributed from thecommerce server 4200 to telephones of the service providers 4209 usingthe radial distribution module 4240 (e.g., that applies the radialalgorithm 4241 using a series of modules working in concert), accordingto one embodiment. The cellular network 2908 may use a set offrequencies from neighboring cells, to avoid interference and provideguaranteed bandwidth within each cell, in one embodiment.

When joined together these cells of the cellular network 2908 mayprovide radio coverage over a wide geographic area through the cellularnetwork 2908 in a manner that ensures that the broadcast data 4202 maybe simultaneously communicated via both IP networks (e.g., to therecipients 4214) and/or to the service providers 4209 through thecellular network 2908. It will be appreciated that the radialdistribution module 4240 (e.g., that applies the radial algorithm 4241using a series of modules working in concert) in effect permitssimultaneous updates to claimed user pages, unclaimed (preseeded) userpages in a geospatially constrained social network 4242 (e.g.,neighborhood social network) based on a geospatial location of the dataprocessing system 4204 in a manner that simulates a radio (RF) basednetwork separately from the concepts described in conjunction with thecellular network 2908. However, it will be understood that the radialdistribution module 4240 (e.g., that applies the radial algorithm 4241using a series of modules working in concert) may be not restricted tosuch topology and can multimodally communicate through differentnetworks, such as through the cellular network 2908 described in FIG.42.

The service providers 4209 may be locations, devices, and/or mobilephones associated with individuals and/or agencies. The serviceproviders 4209 may be notified when a garage sale in a local areaincluding a non-transitory location (e.g., around where they live and/orwork, regardless of where they currently are) and a transitory location(e.g., where they currently are) is posted using the data processingsystem 4204 as the broadcast data 4202.

The service providers 4209 may include the businesses 2922, emergencyservices (e.g., police, firefighters, and/or medical first responders),food related establishments, retail establishments, and/or repairservices). In this manner, data processing systems 4304 and/or desktopcomputers operated by the service providers 4209 may be alerted wheneverthe broadcast data 4202 is posted in and/or around their neighborhoodthrough a push notification (e.g., an alert popping up on their phone),through an email, a telephone call, and/or a voice message delivered tothe particular data processing system operated by each of the serviceproviders 4209 using the radial distribution module 4240 (e.g., thatapplies the radial algorithm 4241 using a series of modules working inconcert).

The broadcast data 4202 may be delivered as notification data 4212 fromthe commerce server 4200 to the recipients 4214 and/or to the serviceproviders 4209 using the radial distribution module 4240 (e.g., thatapplies the radial algorithm 4241 using a series of modules working inconcert) of the commerce server 4200.

The recipients 4214 may be individuals that have claimed a profile(e.g., verified their profile through a postcard, a telephone lookup, autility bill) associated with a particular non-transitory address (e.g.,a home address, a work address) through a geospatial social network(e.g., a geospatially constrained social network 4242 (e.g., aneighborhood social network such as Fatdoor.com, Nextdoor.com)) throughwhich the commerce server 4200 operates. The recipients 4214 may be in ageo-fenced area, in that an epicenter 4244 of a broadcast message fromthe data processing system 4204 (e.g., a data processing system 504) maybe a center through which a radial distance is calculated based on acharacteristic of the broadcast data 4202. For example, a short term job(e.g., moving furniture) may be delivered only to an immediate 0.1 mileradius, and a permanent job opening may be automatically delivered to abroader 0.6 mile radius either automatically and/or through a userdefined preference (e.g., set by the user 2916).

It should be appreciated that individuals in an area outside thethreshold radial distance 4215 may not receive the broadcast data 4202because their geospatial address may be outside a radial boundarysurrounding an epicenter 4244 in which the broadcast data 4202originates. Additionally, the threshold radial distance 4219 may beconfined on its edges by a geospatial polygon at a juncture between areadefined by recipients 4214 and the area outside the threshold radialdistance 4215, according to one embodiment. In one embodiment, theautonomous neighborhood multi-copter 100 may periodically transmit theheartbeat message 4260 to the commerce server 4200. The heartbeatmessage may include the current geo-spatial coordinates of theautonomous neighborhood multi-copter 4262, a time stamp 4264, a datestamp 4266, and/or an operational status of the vehicle 4268.

FIG. 43A shows a form 4302 of an autonomous neighborhood aerial vehicle4300, according to one embodiment. The autonomous neighborhood aerialvehicle 4300 may be comprised of the same systems or similar systems asillustrated in FIG. 1A and FIG. 2. The autonomous neighborhood aerialvehicle 4300 may have the same capabilities as the autonomousneighborhood multi-copter 100. In one embodiment, the autonomousneighborhood aerial vehicle 4300 may not have land based travelcapabilities (e.g., may not have wheels). In one embodiment, theautonomous neighborhood multi-copter may have a detachable storagecompartment 4301 physically associated with it. The storage compartment101 may be detachable from the autonomous neighborhood aerial vehicle4300 and/or may be the same as or similar to the storage compartmentdiscussed in FIG. 1A.

A detachable hook device 4304 may enable the autonomous neighborhoodaerial vehicle 100 to pick up (e.g., hook) a package (e.g., a bag, acontainer, an item) and/or travel (e.g., fly) with the package and/ordrop the package off (e.g., unhook) without human intervention. Theautonomous neighborhood multi-copter 100 (e.g., the autonomousneighborhood aerial vehicle 4300) may have a mobile hooking and/orgrabbing mechanism (e.g., a mechanical arm) capable of securing (e.g.,grasping, hooking, moving, twisting, and/or manipulating) itsenvironment and/or items in its environment. The mobile hooking and/orgrabbing mechanism may have a separate sensor system to enable guidingand/or operating of the mobile hooking and/or grabbing mechanism. In oneembodiment, the autonomous neighborhood aerial vehicle 4300 may havemultiple battery compartments 4306 and/or automatic switch overcapabilities to enable the autonomous neighborhood aerial vehicle 4300to seamlessly switch between batteries (e.g., when one battery runsout). For example, the autonomous neighborhood aerial vehicle 4300 mayhave a battery or set of batteries for the trip to a destination and aseparate battery or set of batteries for the trip back.

FIG. 43B shows the autonomous neighborhood aerial vehicle 4300 of FIG.43A, according to one embodiment. The autonomous neighborhood aerialvehicle 4300 may be capable of being collapsed (e.g., compacted and/orfolded). This collapsing may enable the autonomous neighborhood aerialvehicle 4300 to be more efficiently stored and/or transported. Thedetachable storage compartment 4301 and/or detachable hooking device4304 may be detached. In one embodiment, the autonomous neighborhoodaerial vehicle 4300 may be capable of being collapsed without detachingthe storage compartment 101, as shown in FIG. 43B. In one embodiment,the autonomous neighborhood aerial vehicle 4300 may be portable (e.g.,able to fit in the trunk of a car) when collapsed and/or not collapsed.

In one embodiment, the autonomous neighborhood aerial vehicle 4300 maybe able to be deployed (e.g., given an assignment (e.g., a pick-upand/or delivery) and/or able to execute the assignment) remotely whenstored in the trunk of an autonomous vehicle. For example, an individualmay have an autonomous car and an autonomous neighborhood multi-copter4300. The individual may store their autonomous neighborhood aerialvehicle 4300 in the trunk of their autonomous car. The individual may beout to dinner and realize they left their wallet at home. Rather thanhaving their significant other drive all the way to the restaurant todeliver the wallet or risk losing their parking spot and having to leavethe dinner, the individual may be able to send an order to theirautonomous neighborhood aerial vehicle 4300 through their mobile device(either communicating directly to the autonomous neighborhoodmulti-copter 4300 and/or the autonomous car) to retrieve their walletfrom their house.

The autonomous car may open its trunk and the autonomous neighborhoodaerial vehicle 4300 may be able to situate itself (e.g., unfold and/orconfigure itself into an operational condition) complete the pick-up,delivering the wallet to the restaurant, re-collapse itself, and returnto the trunk of the autonomous car. Rather than missing the dinner orburdening another individual, the individual may be able to retrievetheir wallet by simply walking outside the restaurant and removing theirwallet from the storage compartment.

FIG. 44 is a cross sectional view 4450 of a storage compartment 4400 ofthe autonomous neighborhood multi-copter 100, according to oneembodiment. The storage compartment 4400 may have separate compartments4401 capable of keeping their contents separate from other compartments4401 and/or other items 4502 in the same compartment 4401. Thecompartment(s) 4401 may have a suspension system capable of keeping thecontents of the compartment(s) 4401 stable and/or protected. In oneembodiment, the compartments 4401 may be able to be kept at differenttemperatures and/or humidity levels via the temperature control module246. In one embodiment, the compartments 4401 may be separated bybarriers 4403 capable of absorbing, deflecting, canceling etc.temperatures and able to keep humidity levels and temperatures separatebetween compartments 4401.

In one embodiment, the autonomous neighborhood multi-copter 100 and/orthe storage compartment 4400 may have a loading mechanism 4402 capableof loading items 4502 from any number and/or combination of compartments4401 to the ejection module 110. An air based propulsion system 4406 maywork in concert with the camera adjacent to the ejection module 4408 toeject the object from the ejection module 110 to a targeted destination.In one embodiment, the autonomous neighborhood multi-copter 100 and/orthe storage compartment 4400 may possess multiple ejection modules 110,air based propulsion systems 4406 and/or cameras adjacent to theejection module 4408. The user (e.g., recipient 4214) may be able tomake a payment via a biometric payment reader 4410 on the autonomousneighborhood multi-copter 100.

FIG. 45 is a cross sectional view 4550 of a storage compartment 4500 ofthe autonomous neighborhood multi-copter 100, according to oneembodiment. Particularly, FIG. 45 shows the storage compartment 4500, anitem 4502, and warming trays 4504. In one embodiment, the storagecompartment 4500 may have several trays capable of storing items 4502 onseparate levels. The trays may be warming trays 4504 capable of warmingitems (e.g., pizza boxes) placed on the tray and/or cooling trayscapable of cooling items 4502 placed on the tray (not shown). Asuspension device 4506 may keep the item 4502 stable in transit and/ormay absorb shocks and/or correct for forces acting on the interior ofthe storage compartment 101. The recipient 4214 may be able to pay usinga magnetic card reader 4508 on the autonomous neighborhood multi-copter100.

FIG. 46A is a sidewalk traversing view 4650 of the autonomousneighborhood multi-copter using the telescoping platform to mount asidewalk, according to one embodiment. The sidewalk detection sensor 111may detect that a sidewalk is present (e.g., blocking the path of theautonomous neighborhood multi-copter 100) by sensing a gradation rise4600 of a sidewalk start location 4602. The telescoping platform 107 mayelevate the autonomous neighborhood multi-copter 100 from the roadway114 so that the wheels are level with the surface of the sidewalk 112.The telescoping platform may shift the autonomous neighborhoodmulti-copter 100 in such a way that the wheels meet the sidewalk 112surface.

Once the rest of the autonomous neighborhood multi-copter 100 issecurely on the surface of the sidewalk 112, the telescoping platform107 may return (e.g., re-ascend and/or collapse) itself to its originalposition and/or orientation (e.g., at the base of the autonomousneighborhood multi-copter 4601 now located on the sidewalk 112). In oneembodiment, the telescoping platform may be capable of rotating 360degrees around a vertical axis, allowing the autonomous neighborhoodmulti-copter 100 to mount the sidewalk 112 at a 90 degree angle fromwhere it was facing on the roadway 114. It will be appreciated by onewith skill in the art that other methods for raising and/or lowering theautonomous neighborhood multi-copter 100 so as to traverse a gradationchange are possible.

FIG. 46B is a sidewalk traversing view 4651 of the autonomousneighborhood multi-copter using the telescoping platform to dismount asidewalk, according to one embodiment. The sidewalk detection sensor 111may detect that a sidewalk is ending by sensing a gradation drop 4604 ofa sidewalk end location 4606. In one embodiment, the telescopingplatform 107 may first lower a set of front wheels 4608 to the roadway114. The autonomous neighborhood multi-copter 100 may move itselfforward off the sidewalk 112 with its set of front wheels 4608 on theroadway 114 and its rear wheels on the sidewalk 112. Once the rearwheels reach the sidewalk end location 4606, the rear wheels mayseamlessly be lowered to the roadway in a manner such that the contentsof the autonomous neighborhood multi-copter 100 are not disturbed by thechange in elevation. Other methods for raising and/or lowering theautonomous neighborhood multi-copter to traverse gradation changes arepossible. FIG. 46B also shows a pattern 4608 of the wheels allowing theautonomous neighborhood multi-copter to traverse obstacles and/ordifferent terrains. A remote sensing capability 4612 of the autonomousneighborhood multi-copter 100.

FIGS. 47-51 illustrate collision identification view 4750, 4850, 4950,5050, and 5150 of exemplary steps for rapidly identifying the locationof the potential collision. FIG. 47 illustrates the trajectory path 4700(e.g., the optimal route 802) of the autonomous neighborhoodmulti-copter 100 and the trajectory path 4702 of another entity (e.g., acar, another autonomous neighborhood multi-copter 100, a bicycle, ananimal). The trajectory path 4700 of the autonomous neighborhoodmulti-copter 100 is viewed as a plurality of line segments with eachline segment constructed between positions of time.

For example, a first line segment is represented by a line constructedbetween t_(h(0)) and t_(h(1)), a second line segment is represented by aline constructed between t_(h(1)) and t_(h(2)), and so forth. Thetrajectory path of another entity is also viewed as line segmentsconstructed between time positions. For example, a first line segment isrepresented by a line constructed between t_(r(0)) and t_(r(1)), asecond line segment is represented by a line constructed betweent_(r(1)) and t_(r(2)), and so forth. The location of the potentialintersection of the trajectory path 4700 of the autonomous neighborhoodmulti-copter 100 and the trajectory path 4702 of the another entity isat a location where the line segment of the autonomous neighborhoodmulti-copter 100 represented by t_(h(n-1)) and t_(h(n)), hereinafterreferred to as line segment 4704, intersects with line segment of theanother entity represented by t_(r(n-1)) and t_(r(n)) t_(h(n))hereinafter referred to as line segment 4706. A determination of wherethe intersection is located can be computationally extensive if all linesegments of the autonomous neighborhood multi-copter 100 and the linesegments of the another entity required intersecting analysis. That is,a comprehensive analysis would require that the first line segment ofthe trajectory path 4700 of the autonomous neighborhood multi-copter 100and the first line segment of the trajectory path 4702 of the anotherentity are analyzed to determine if an intersection is present.

If no intersection exists, then the first line segment of the trajectorypath 4700 of the autonomous neighborhood multi-copter 100 issequentially checked for an intersection with all the remaining linesegments of the trajectory path 4702 of the another entity. If nointersection is detected, then a second line segment of the trajectorypath would be sequentially analyzed for an intersection with all theline segments of the trajectory path 4702 of another entity. Eachremaining line segment of the trajectory path 4700 of the autonomousneighborhood multi-copter 100 would be sequentially analyzed with theeach line segment of the trajectory path 4702 of the another entityuntil an intersection is detected. Depending on the number of linesegments, such an assessment could be time consuming and computationallyextensive.

The advantage of the embodiments described herein provides for a rapidassessment for determining the intersection of the two trajectory paths.As illustrated in FIG. 47, a boundary box 4708 is constructed around thetrajectory path boundary 4710, and a boundary box 4712 is constructedaround the trajectory path boundary 4714. Boundary boxes 4708 and 4712,in the shape of rectangles, form envelopes (separate from the envelope900) around the entire trajectory path boundary of each vehicle and/orentity.

In FIG. 48, midway position index locations of each boundary box 4708and 4712 are identified as represented by position indexes 4800 and4802, respectively. It should be understood that the midway of the indexlocations that contain the boundary box is used to divide the boundarybox into portions, which may not be the midway point of the boundary boxitself. Therefore, the subdivided boundary boxes may not be equalhalves. Position indexes containing the boundary box 4708 and 4712 areeach subdivided into two portions at the position indexes 4800 and 4802.The subdivided boundary boxes of each respective trajectory path thatcontain the intersecting line segments 4704 and 4706 are selected asrepresented by 4804 and 4806.

In FIG. 49, subdivided boundary boxes 4804 and 4806 are regenerated. Theboundary boxes may be regenerated by either the length and/or widthbased on the trajectory path of each entity (e.g., the autonomousneighborhood multi-copter 100 and/or the another entity). Theregenerated boxes are not required to align to a same axis the previousboundary boxes were positioned. Rather, the routine allows each boundarybox to be configured to the targeted portion of the trajectory path thatthe routine is analyzing. As a result, the boundary box can berepositioned to accommodate to varying change of directions along thetrajectory path. For each regeneration, the boundary boxes areconfigured adapt to the trajectory paths at the location of thecollision.

In FIG. 50, the midway position index locations of each regeneratedboundary box 4804 and 4806 are identified. Boundary boxes 4804 and 4806are further subdivided into portions using the position indexes 4900 and4902. The intersection of the subdivided portions is determined and anext set of intersecting boundary boxes are regenerated. The next set ofregenerated boundary boxes includes the intersection of the trajectorypaths. The routine repeatedly subdivides and regenerates the boundaryboxes until only the respective intersecting line segments 4704 and 4706are contained within the final boundary boxes. It should be understoodthat the subdividing of the boundary boxes may require more or lesssubdividing than what is shown. The subdividing of the boundary box endswhen a respective remaining boundary box contains only two of theposition index locations. The two positions will form line segment.

FIG. 51 illustrates a final set of regenerated boundary boxes 5100 and5102 where the line segments 4704 and 4706 intersect within theirrespective margins. As is shown, the only line segments that aredisposed within each respective boundary box are their respective linesegments. It should be understood that the technique described can useda set of index positions for identifying the intersection as opposed tothe line segments. For example, it is determined that the intersectionoccurs between t_(h(n-1)) and t_(h(n)) for the autonomous neighborhoodmulti-copter 100, and that the respective boundary box for theautonomous neighborhood multi-copter 100 could be subdivided andregenerated based on the boundary box containing the set of pointindexes t_(h(n-1)) and t_(h(n)) in contrast to a line segment. While theabove method for collision identification has been described in thecontext of land based travel, it will be appreciated by one with skillin the art that this method may be applied to identifying collisions inaerial environments and/or travel.

FIG. 52 is an intersection view 5250 of the autonomous neighborhoodmulti-copter 100 functioning at an intersection, according to oneembodiment. As the autonomous neighborhood multi-copter 100 approachesan intersection, it may use its various components (e.g., sensor system102) to detect the vehicle's location as well as objects external to thevehicle. For example, autonomous neighborhood multi-copter 100 may usedata from the geographic position component (e.g., the globalpositioning system 218) to identify location coordinates or an addressassociated with the current location of the autonomous neighborhoodmulti-copter 100. The autonomous neighborhood multi-copter 100 may thenaccess road-graph data corresponding to this location.

The autonomous neighborhood multi-copter's 100 computer system 200 mayuse data from the sensor system 102 to detect objects in the autonomousneighborhood multi-copter's 100 surroundings (e.g., the environment ofthe autonomous neighborhood multi-copter 152). As the sensor (e.g.,laser, camera 226, ultrasound unit 228) moves along, it may collectrange (distance) and intensity information for the same location (pointor area) from several directions and/or at different times. FIG. 52depicts an exemplary display of sensor data collected as the autonomousneighborhood multi-copter 100 approaches an intersection 5200. Forexample, the autonomous neighborhood multi-copter 100 may be able todetect lane lines, a crosswalk 5202, traffic signs and/or lights etc. aswell as their locations relative to the current location of theautonomous neighborhood multi-copter 100. This relative locationinformation may be used to identify an actual location of the object. Insome examples, the computer system 200, sensor fusion algorithm 238and/or sensor system 102 may use the road-graph and data from the sensorsystem 102 to increase the accuracy of the current location of theautonomous neighborhood multi-copter 100, for example by comparing lanelines of intersection 5200 to lane lines of the road-graph, etc. In oneembodiment, the autonomous neighborhood multi-copter 100 may be able tonavigate autonomously without use of and/or need for lane lines. In oneembodiment, the autonomous neighborhood multi-copter 100 may stop at aminimum crosswalk proximity 5304. The autonomous neighborhoodmulti-copter may identify (e.g., sense and/or identify) a stop sign5206, a yield sign 5208 and/or a traffic light) and proceedappropriately.

In addition to detecting fixed objects, the computer system 200, sensorfusion algorithm 238 and/or sensor system 102 may also detect theexistence and geographic location of moving objects (e.g., the bicyclist302, the a car, the pedestrian 804 and/or an animal). The computersystem 200, sensor fusion algorithm 238 and/or sensor system 102 maydetermine whether an object is moving or not based on the autonomousneighborhood multi-copter's 100 own speed and acceleration, etc., andthe data received from the sensor. For example, as shown in FIG. 52, thesensor data may be used to detect objects 610,611, and 620,corresponding to the pedestrians and bicyclist of FIG. 48, as well astheir locations relative to the current location of the vehicle. Thisrelative location information may be used to identify an actual locationof the object. After some short period of time where the bicyclist andpedestrians have moved, computer 110 may determine that these featuresare moving based on a change in their location relative to intersection5200.

Once the various objects in the environment of the autonomousneighborhood multi-copter 152 have been detected, they may be comparedto the road-graph in order to identify what the objects are. Forexample, the autonomous neighborhood multi-copter 100 may identify lanelines from the laser data as lane lines of the road-graph. However,objects (e.g., a bicyclist 306E, a bicyclist 306F, a pedestrian 904Cand/or a pedestrian 904D) will not appear on the road-graph as they arenot static objects expected to reappear each time the autonomousneighborhood multi-copter 100 drives through intersection 5200.

These moving (or non-static) objects may also be compared to theroad-graph data for identification. Objects which are located completelyor partly within a pre-defined area of the road-graph may be identifiedbased on the area identifier. The geographic locations of the objectsmay be compared to the corresponding geographic locations in theroad-graph. Objects may be identified by the autonomous neighborhoodmulti-copter 100 as pedestrians based on their location (e.g., in thecrosswalk 5202). Similarly, bicyclists 302E and 302F appear within bikelane 307, and the autonomous neighborhood multi-copter 100 may identifythe objects as a bicyclists based on their location in the bicycle lane304 identifier, shape and/or speed.

Not every object observed in the pre-defined areas will necessarily be apedestrian (or bicyclist). For example, other vehicles (e.g. scooters,cars, trucks) may also pass through crosswalks or move into bicyclelanes. In this regard, the identifier associated with a pre-defined areamay be a hint or indication that objects in these areas may be morelikely to be pedestrians or bicyclists. For example, the autonomousneighborhood multi-copter's 100 computer system 200 and/or sensor fusionalgorithm 238 may consider a variety of sensor data and map data whichmay indicate a moving object's type. These indications may include laserpoint cloud density, surface normal distribution, object height, objectradius, camera image color, object shape, object moving speed, objectmotion in the past N seconds, etc. The autonomous neighborhoodmulti-copter 100 may then consider the object's type based on the sum ofthese indications, for example, by using a machine learning algorithmwhich classifies the type of object. In one example, the machinelearning algorithm may include various decision trees. The pre-definedregions may therefore allow the computer to identify certain objects,such as pedestrians and bicyclists, faster.

If the moving object cannot be identified based on the area identifiers,other identification methods may be used. For example, image and patternmatching techniques involving comparing one or more images (or laserdata) of the moving object to a set of pre-identified images (or laserdata), may be used to identify the moving object.

Once the moving objects have been identified, the computer system 200may use this information to control the autonomous neighborhoodmulti-copter 100. The computer system 200 may operate the autonomousneighborhood multi-copter 100 in order to avoid injury to nearby peopleor the autonomous neighborhood multi-copter 100 by maintaining a safeminimum distance, for example several yards, from pedestrians orbicyclists while the autonomous neighborhood multi-copter is moving. Forexample, an autonomous neighborhood multi-copter 100 may stop where thepedestrian 904D is identified in the crosswalk 5250 in front of theautonomous neighborhood multi-copter 100, or the autonomous neighborhoodmulti-copter 100 may not pass the bicyclist 302F unless the autonomousneighborhood multi-copter 100 is able to maintain the minimal distance(e.g., in compliance with the envelope 900). In another example, thetype of action may be based on the object detected by the autonomousneighborhood multi-copter 100 and/or the conditions in which theautonomous neighborhood multi-copter operates (e.g., the state of theenvironment of the autonomous neighborhood multi-copter 152).

For example, the autonomous neighborhood multi-copter may have a largerminimum distance at which it may stop at crosswalks 5202 when it israining and/or may have a larger minimum distance that must bemaintained between the autonomous neighborhood multi-copter 100 and apedestrian than between the autonomous neighborhood multi-copter 100 anda traffic cone. In one embodiment, before the autonomous neighborhoodmulti-copter 100 may continue along its route (e.g., enter theintersection, make a turn, continue to move), the pedestrian 904D mayhave to clear the crosswalk 5202 and/or the roadway 114. The bicyclist302E may be required to exit the intersection 5200 before the autonomousneighborhood multi-copter 100 may continue along its route.

FIG. 53 is a user interface view 5350 of the data processing system 4204showing the autonomous neighborhood multi-copter in a neighborhood,according to one embodiment. The user of the autonomous neighborhoodmulti-copter 100 (e.g., the user 2916, a renter and/or an owner) may beable to view the location of the autonomous neighborhood multi-copter100 on a neighborhood map on the data processing system 4204. The user(e.g., the user 2916) may be able to select options on the dataprocessing system 4204. A stop function may allow the user to remotelystop the autonomous neighborhood multi-copter 100, a go function mayallow the user to remotely make the autonomous neighborhood multi-copter100 move and/or begin the task submitted by the user. In one embodiment,the autonomous neighborhood multi-copter 100 may operate in the limit ofthe Wi-Fi connection with the control device and/or commerce server4200. The user may be able to select a destination on the autonomousneighborhood multi-copter map 5300, set an altitude and/or cruisingspeed (e.g., speed 5307).

The user may be able to change the route taken by the autonomousneighborhood multi-copter, the destination and/or return location byselecting a reroute function. A change details function may allow theuser to alter aspects of the task (e.g., pick-up and/or delivery). Theuser may be able to update a shopping list, alter a desired pick-upand/or drop-off time, alter humidity levels, alter temperature, alterconstrains of the autonomous neighborhood multi-copter (e.g., theenvelope 900 and/or a maximum speed). In one embodiment, the autonomousneighborhood multi-copter may have set constraints that may not bealtered and/or have set ranges that allow users to alter constraintswithin the set ranges. The user may be able to select a switch viewsfunction that may enable the user to switch between an aerial view(shown in FIG. 53), a street view (e.g., a view through the camera 226),a view through any other sensor and/or a rear view). A “take off”function may enable the user to signal to the autonomous neighborhoodmulti-copter 100 to begin its task. A rescue function may contact repairservices and/or notify the owner of the autonomous neighborhoodmulti-copter if there is an issue (e.g., breakdown, blown tire, theautonomous neighborhood multi-copter gets stuck).

The user interface may show an autonomous neighborhood multi-copter map5300 with a current location of the autonomous neighborhood multi-copter5406 (shown in FIG. 54), a geospatial vicinity 5302, a neighborhoodboundary 5303, the neighbor 2920, a destination 5306, and/or otherautonomous neighborhood multi-copters 100. In one embodiment the usermay be able to view the profile of the neighbor 2920 and/or createbi-directional communication with the neighbor 2920 (e.g., request touse their autonomous neighborhood multi-copter 100) by selecting theneighbor's icon on the map of the neighborhood 1402A (e.g., theautonomous neighborhood multi-copter map 5300. The user may be able toview a starting address 5308 of the autonomous neighborhood multi-copter100, a destination address 5312, and/or a merchant 5310 and/ordestination 5306.

In one embodiment, the user (e.g., user 2916) may be able to record avideo and/or audio (e.g., using the sensor system 102 of the autonomousneighborhood multi-copter 100), take pictures, alter the speed, alterthe temperature of the storage compartment 101 (e.g., using thetemperature control module 246), and/or order the autonomousneighborhood multi-copter to return (e.g., to the start location (e.g.,start address 5308), claimed geo-spatial location and/or the userlocation 5408). The user may be able to view the amount of energy of theautonomous neighborhood multi-copter 100 that remains. In oneembodiment, the user may be able to view a radius (e.g., maximumdistance) the autonomous neighborhood multi-copter is able to travel. Inone embodiment, the user may be able to view a time to arrival 5412(shown in FIG. 54). Altering the speed may include increasing and/ordecreasing the speed 5307. In one embodiment, a range of speed 5721 maybe a minimum and/or a maximum speed at which the autonomous neighborhoodmulti-copter 100 may travel. A predetermined interval 5374 may be setautomatically or by the user for when the autonomous neighborhoodmulti-copter 100 determines is a different route that is more efficientthan the optimal route exists. The autonomous neighborhood multi-copter100 may calculate the route and travel along the route once it isdetermined to exist.

FIG. 54 is an autonomous neighborhood multi-copter alert user interfaceview 5450 of a data processing system 4204 receiving an autonomousneighborhood multi-copter alert, according to one embodiment.Particularly, FIG. 49 shows an autonomous neighborhood multi-copteralert 1302, the autonomous neighborhood multi-copter map 5300, theautonomous neighborhood multi-copter's current location 5406, a userlocation 5408, a delivery details 5410, the recipient 4214, a time toarrival view 5412, an action selector 5414, action 5416A, action 5416B,action 5416C, a non-transient location 5418, a credit payment 5420, aparticular user 5422, a delivery time 5412, a minimum travel distance5426, a minimum travel distance per trip 5428, minimum travel distanceper day 5432, and minimum travel distance per delivery 5430.

In one embodiment, the user 2916 (e.g., owner of the autonomousneighborhood multi-copter, user of the autonomous neighborhoodmulti-copter) may be able to receive autonomous neighborhoodmulti-copter alerts 5402 on the data processing system 4204 associatedwith the user 2916. The autonomous neighborhood multi-copter alert 5402may alert the user 2916 when the autonomous neighborhood multi-copter100 arrives at the destination 5306, departs from the destination 5306,when items 4502 (shown in FIG. 45) have been removed and/or added, whenstuck (e.g., at a traffic light, in traffic, in a ditch), when abreakdown occurs, when a certain amount of time has elapsed, when athreshold distance traveled has elapsed, when energy levels reach athreshold level, when another user requests to use (e.g., rent) theautonomous neighborhood multi-copter 100, when the lock 1218 has beentampered with, when there is an attempted theft etc.

The user 2916 (e.g., the owner of the autonomous neighborhoodmulti-copter) may be able to view the autonomous neighborhoodmulti-copter map 5300 via the data processing system 4204. In oneembodiment, the autonomous neighborhood multi-copter map 5404 maydisplay the current autonomous neighborhood multi-copter location 5406and/or the user location 5408 (e.g., the user's current location and/orthe claimed geospatial location 700). The autonomous neighborhoodmulti-copter map 5300 may also display the destination 5306, accordingto one embodiment. In another embodiment, other users of thegeospatially constrained social network 4242 may be able to view thecurrent location of the autonomous neighborhood multi-copter 5406 and/ormay be able to request use of the autonomous neighborhood multi-copter100 if the autonomous neighborhood multi-copter 100 (e.g., autonomousneighborhood aerial vehicle 4300) is within a threshold radial distance4219 from the location of the other users (e.g., current location and/orclaimed location(s)).

The delivery details 5410 may allow the user to view confirmation that atask (e.g., a delivery and/or a pick-up) has been completed, that theitem 4502 (shown in FIG. 45) has been placed in the autonomousneighborhood multi-copter 100, to indicate a status of the autonomousneighborhood multi-copter 100 etc. In one embodiment, a financialtransaction may be completed through the commerce server 4200. The user2916 (e.g., owner of the autonomous neighborhood multi-copter and/orsender of the items delivered by the autonomous neighborhoodmulti-copter) may be able to see account information and/or the profileof the recipient 4214 and/or alter their own account information via thedata processing system 4204. The other user (e.g., the recipient of thedelivery) may be able to submit comments to the user 2916 (e.g.,information about the delivery, a thank you, a request for furtherdeliveries, a request for use of the autonomous neighborhoodmulti-copter etc.).

The time to arrival view 5412 may indicate the time (e.g., timeremaining, estimated time of arrival) until the autonomous neighborhoodmulti-copter 100 arrives at its destination 5306 and/or returns from itsdestination 5306. The action selector 5414 may allow the user to selectan action in response to the autonomous neighborhood multi-copter alert5402. In one embodiment, the user may select any number of actions(e.g., action 5416A and/or action 5416B and/or action 5416C). Action5416A may enable the user to contact the destination (e.g., theindividual, the shop, the company) and/or establish bi-directionalcommunication. Action 5416B may allow the user to contact repairservices (e.g., in the case of a break down). Action 5416C may allow theuser to command the autonomous neighborhood multi-copter 100 to returnto the user's location (e.g., the owner's current location and/or theowner's claimed geospatial location(s), the user's (e.g., renter's)current location). In one embodiment, the user may be able to allowother users to user (e.g., rent) the autonomous neighborhoodmulti-copter 100 via the action selector 5414, change a destination,and/or add additional destinations to the route.

FIG. 55 is a three dimensional environmental view 5500 of the laserrangefinder/LIDAR unit of the sensor system creating a map of theenvironment of the autonomous neighborhood multi-copter, according toone embodiment. The laser rangefinder/LIDAR unit 224 of the autonomousneighborhood multi-copter's 100 sensor system 102 may use multiplelasers to map its surroundings, measuring a time-to-distance correlationof each laser in a series to capture the distance data from each point.The multiple lasers may be emitted in such a way that a 360 degree scanmay be gathered. This may allow the autonomous neighborhood multi-copterto gather very large amounts of data in a short amount of time, creatingdetailed scans of its surroundings.

In the embodiment illustrated in FIG. 55, the sensor system 102 of theautonomous neighborhood multi-copter 100 detects multiple objects in itsenvironment. The autonomous neighborhood multi-copter 100 may, using thesensor fusion algorithm 238, be able to identify an object 408A as apedestrian based on its shape, speed and/or location (e.g., on thesidewalk). An object 408B may be identified as a car based on similarcriteria. In one embodiment, the autonomous neighborhood multi-copter100 may have multiple laser rangefinder/LIDAR units 224 so that a 360degree scan can be achieved. In one embodiment, the three dimensionalenvironmental view 5500 may be captured and/or created by multiplesensors working in concert.

FIG. 56 is a garage view 5650 of a garage structure 5600 contacting twopassenger vehicles 5604 (autonomous cars), an operator of the autonomousneighborhood multi-copter 5602, and an autonomous neighborhoodmulti-copter 100, according to one embodiment. Individuals may be ableto purchase the autonomous neighborhood multi-copter 100 and/or store itin their garage. Families may have multiple autonomous cars forpersonnel transportation along with the autonomous neighborhoodmulti-copter 100 for running errands. In the shown embodiment of FIG.56, the autonomous neighborhood multi-copter 100 has an internal sensorsystem (e.g., no sensors mounted on top of or on the surface of theautonomous neighborhood multi-copter). The autonomous cars are shownwith one having a top mounted sensor system 102 (e.g., a LIDAR sensor)and one having an internal sensor system (e.g., a non-surface mountedsensor system).

FIG. 57 is an emergency broadcast view 5750 of the data processingsystem of FIG. 42 receiving an emergency broadcast message, according toone embodiment. Particularly, FIG. 57 shows an emergency broadcastmessage 5702, a failure condition 5703, an impact 5704, an accident5705, a mechanical failure 5706, a crime 5707, an electrical failure5708, an attempted tampering 5709, a video data 5710, a fire station5711, an audio data 5712, a police station 5713, a photo data 5714, amedical responder 5715, a time out 5716, a damage condition 5718, ageo-spatial coordinates data 5720, a longitudinal data 5722, alatitudinal data 5724, an event 5726, an occurrence 5728, an onlinecommunity 5730, a map 5734, a geospatial representation of a set ofpoints 5736, a member data 5738, an address 5740, a profile 5742, apersonal address privacy preference 5744, a verification 5746, and aparticular residential address 5748.

In one embodiment, the emergency broadcast message 5702 may be sent tothe data processing system 4204 of a recipient 4214 having a verifiedaddress in a threshold distance from the event (e.g., the occurrence5728 of the failure condition 5703). In one embodiment, the emergencybroadcast message 5702 may be sent to a service provider 4209 (e.g., thefire station 5711, the police station 5713, and/or the medical responder5715). The recipient 4214 of the emergency broadcast message 5702 may beable to respond to the message, see the location of the event 5726 onthe map 5734 (e.g., the current location of the autonomous neighborhoodmulti-copter 5406), view video data 5710, audio data 5712, photo data5714 and/or the geo-spatial coordinates data 5720. In one embodiment,the user (e.g., the recipient 4214) may be able to view and/or altertheir profile and/or information (e.g., address 5740 and/or personaladdress privacy preference 5744) on the data processing system 4204.

FIG. 58A is a weather traversing view 5850 of the autonomousneighborhood multi-copter 100 traveling in windy conditions. The sensorsystem 102 and/or air control system 247 of the autonomous neighborhoodmulti-copter 100 may detect weather patterns, disturbances, wind,turbulence etc. and/or the autonomous neighborhood multi-copter 100 mayuse information about such conditions (e.g., from a weather dataprovider) to effectively travel in different sets of weather conditions119. In the embodiment shown in FIG. 58A, the autonomous neighborhoodmulti-copter 100 may account for a weather force to the left 5802 and/ora weather force to the right 5802. The weather forces may impact theautonomous neighborhood multi-copter's 100 ability to remain on theflight path 120 and/or may make the flight path 120 (e.g., the optimalroute 802) no longer desirable and/or possible. The autonomousneighborhood multi-copter 100 may identify and/or take the differentroute 804A and/or be forced to land (e.g., abandon the task and/orswitch to a driving mode using wheels on the ground. In one embodiment,the optimal route may comprise of aerial and land-based travel sections(and/or aquatic sections).

In the embodiment of FIG. 58A, the autonomous neighborhood multi-copter100 may calculate the different route 804A using information about theweather forces to the left and/or to the right. In the illustratedembodiment, the autonomous neighborhood multi-copter 100 may determinethat the weather force to the left 5802 will force the autonomousneighborhood multi-copter 100 from the flight path 120. However, it mayalso determine that the weather force to the right 5804 will act tocorrect this digression. Thus, the autonomous neighborhood multi-copter100 may determine that no corrective measures are needed as theautonomous neighborhood multi-copter 100 will return to the flight pathon its own (or with only minimal correction that does away will a needto actively determine and/or take an alternate path).

The weather traversing view 5851 of FIG. 58B illustrates an alternateembodiment in which the autonomous neighborhood multi-copter 100determines that corrective measures are necessary. In the shownembodiment, the autonomous neighborhood multi-copter 100 may determinethat the weather force to the left 5802 is much stronger than theweather force to the right 5804. Thus, the autonomous neighborhoodvehicle 100 may take the different route 804B, veering from the flightpath 120 to the right. The weather force to the left (e.g., wind) mayforce the autonomous neighborhood multi-copter 100 back to and past theflight path 120. However, the autonomous neighborhood multi-copter 100may determine that the weather force to the right 5804 will largelycorrect the digression. The autonomous neighborhood multi-copter 100 maydetermine that this correction is sufficient to allow the autonomousneighborhood multi-copter 100 to maximize efficiency of travel andlargely maintain the flight path 120. In other embodiments, theautonomous neighborhood multi-copter may leverage and/or adapt toweather and other aerial travel conditions to maximize efficiency.

FIG. 59 is an aerial traffic navigation view 5950 of autonomousneighborhood multi-copters 100C-E operating in the same air space. Theautonomous neighborhood multi-copter 100C may determine that the flightpath 120A of the autonomous neighborhood multi-copter 100D and flightpath 120 B of the autonomous neighborhood multi-copter 100E are in acollision course with the autonomous neighborhood multi-copter's 100Cflight path 120C. The autonomous neighborhood multi-copter 100C mayalter its course to avoid a collision. In one embodiment, if theautonomous neighborhood multi-copter 100C determines that autonomousneighborhood multi-copters 100D and 100E will collide, the autonomousneighborhood multi-copter 100C may select a different route that iscleared of the anticipated collision.

In one embodiment, the autonomous neighborhood multi-copters 100C-E maybe able to communicate with one another (e.g., through the wirelesscommunication system 251) in order to coordinate alternate flight paths.This may prevent autonomous neighborhood multi-copters from selectingalternate flight paths (in order to avoid the first collision) that arestill conflicting. By communicating different flight paths 804 (e.g.,alternate flight paths) with one another, the autonomous neighborhoodmulti-copters can avoid creating collisions while trying to avoid theoriginal collision. In one embodiment, a prioritization algorithm may beapplied in order to avoid cycling (e.g., never ending selecting ofalternate routes by all entities involved). In one embodiment of theprioritization algorithm, the autonomous neighborhood multi-copter 100traveling the fastest may be prioritized first, having its courseselected as a default. Other autonomous neighborhood multi-copters 100with conflicting flight paths may reroute around the default path. Othermethods for selecting an order and/or system of establishing alternateroutes in order to avoid collisions are possible.

FIG. 60 is a notification graphical process flow 6050 of an order beingdelivered, according to one embodiment. Particularly, FIG. 60 shows anorder 6000, a delivery notification 6002, an order detail view 6004, aprice 6006, a closest multi-copter 6008, a multi-copter availability6010, and a commercial user location 6012. Circle 1 shows the user 2916using the data processing system 4204 to place an order 6000 for apizza. In one embodiment, the user 4204 may access the website of acommercial user 4100 (e.g., Bob's Pizza) and/or log in to thegeospatially constrained social network 4242 (e.g., Fatdoor.com). Theuser may be able to call the commercial user 4100, according to oneembodiment. The user 2916 may select a claimed geospatial locationassociated with the user 2916 (e.g., a guest access address, a workaddress and/or a home address (e.g., the claimed residential address5378)) as the destination 5306 for the delivery.

Circle 2 shows the data processing system 4204 displaying an orderdetail view 6004. In one embodiment, the user 2916 may be able to inputand/or view the order 6000, a price 6006, and/or make a credit payment5420 using the order detail view 6004. The user 2916 may be able toselect a method of attaining the order (e.g., pick up, delivery and/ordine in). In one embodiment, a delivery method may include multi-copterdelivery. Delivery (e.g., multi-copter delivery) may include anadditional charge (e.g., 5 dollars). The order detail view 6004 may showa multi-copter availability 6010. In one embodiment, the multi-copteravailability 6010 may show the number, location, estimated wait time(e.g., estimated time of arrival and/or estimated time of delivery) etc.of available autonomous neighborhood multi-copters 100 in the user's2916 neighborhood 2902. The user 2916 may be able to view a closestmulti-copter 6008 (e.g., the autonomous neighborhood vehicle 100 in thenearest geographic proximity to the destination 5306 and/or thecommercial user 4100, the autonomous neighborhood multi-copter 100 withthe fastest estimated time of arrival and/or estimated time of delivery,the autonomous neighborhood multi-copter 100 with the least amount ofdistance to travel to complete the delivery).

In one embodiment, the user 2916 may be able to view an autonomousneighborhood multi-copter map 5300. The autonomous neighborhoodmulti-copter map 5300 may display the destination 5306, user location5408 (e.g., destination 5306), the commercial user location 6012, and/orthe current locations of the autonomous neighborhood multi-copters 5406.In one embodiment, the user 2916 may receive notifications at each stepof the delivers (e.g., when the autonomous neighborhood multi-copter 100begins the delivers, when it receives the order 6000, and/or when itarrives at the destination) and/or may be able to track the progress ofthe autonomous neighborhood multi-copter 100 on a map (e.g., theautonomous neighborhood multi-copter map 5300). In one embodiment, thecommerce server 100 may take into account preparation time (e.g.,cooking time) while calculating availability of the autonomousneighborhood multi-copters 100, which multi-copter is the closestmulti-copter 6008, and/or when delivery may be completed. The user maybe able to reserve an available autonomous neighborhood multi-copter 100and/or reserve any autonomous neighborhood multi-copter 100 in theneighborhood 2902. In one embodiment, the user 2916 may be able make itso the closest multi-copter 6008 is automatically selected (e.g.,reserved). A reserved autonomous neighborhood multi-copter 100 mayautomatically begin the delivery of the order 6000 once it becomesavailable (e.g., completes orders prioritized (e.g., placed, belongingto a VIP user, going to a certain destination) before the order 6000and/or when the order is ready to be picked-up).

Circle 3 shows the autonomous neighborhood multi-copter 100 at thelocation of the commercial user 4100. In the embodiment of FIG. 60, thecommercial user 4100 is shown as Bob's Pizza. In this embodiment, thecommercial user 4100 (e.g., an employee) may receive an alert that theautonomous neighborhood multi-copter 100 has arrived to execute order6000. The ordered items (e.g., the pizzas) may be loaded into thestorage compartment 101. The commercial user 4100 (e.g., the employee)may use the user interface 104 and/or the data processing system 4204 tosend the autonomous neighborhood multi-copter 100 to the destination5306 and/or confirm that the order 6000 was placed in the storagecompartment 101. In one embodiment, the autonomous neighborhoodmulti-copter 100 may be able to sense that an item was placed into thestorage compartment and/or may automatically complete the delivery uponreceiving the item.

Circle 4 shows the autonomous neighborhood multi-copter 100 at thedestination 5306. In one embodiment, the autonomous neighborhoodmulti-copter 100 and/or commerce server 4200 may send a deliverynotification 6002 to the data processing system 4204 associated with theuser 2916 when the autonomous neighborhood multi-copter 100 has arrivedor is in a set proximity to the destination (e.g., a set distance and/ora set amount of time away). In one embodiment, the proximity may be setby the user 2916 and/or the commerce server 4200. The user 2916 may beable to view the delivery notification 6002 and/or confirm the delivery,add a tip, send the multi-copter back to its non-transient location, thelocation of the commercial user 4100, and/or originating location, senda message and/or rating to the commercial user 4100, and/or place anadditional order using the data processing system. In one embodiment,the autonomous neighborhood multi-copter 100 may be equipped with aspeaker and/or may be able to announce its arrival, record a message,and/or play a message.

FIG. 61A is a view of a neighborhood flying football 6100A, according toone embodiment. Particularly, FIG. 61A shows a set of propellers 6102, apower source 6104, a USB port 6106, a camera 6108, a storage compartment6110, and a body 6112. In one embodiment, the set of propellers 6102 maybe the propellers 113 and/or function in the same or similar way to thepropellers 113. The set of propellers 6102 may include any number ofpropellers aligned in a manner to provide stability and/or flightefficiency to the neighborhood flying football 6100A while in flight. Inone embodiment, the neighborhood flying football 6100A may be theautonomous neighborhood multi-copter 100, the autonomous neighborhoodaerial vehicle 4300, and/or the neighborhood flying football 6100B(shown in FIG. 61B) and/or have the same or similar components,functions, capabilities etc. as the autonomous neighborhood multi-copter100, the neighborhood flying football 6100B and/or autonomousneighborhood aerial vehicle 4300.

In one embodiment, the set of propellers 6102 may be removable from thebody 6112 of the neighborhood flying football 6100A. The body 6112 maybe in the form of a football, a basketball, a soccer ball, and/or anyother recreational object. In one embodiment, the body 6112 in the shapeof a football (as shown in FIG. 61A) may be balanced and capable ofbeing effectively thrown and/or caught like any other football whendetached from the set of propellers 6102. The body 6112 may comprise ofNERF© material, other types of foam, and/or any other material capableof being lifted by the propellers and thrown and/or caught.

According to one embodiment, the camera 6108 may be set (e.g., imbedded,set into and/or on) the nose (e.g., the front nose) of the body 6112. Inone embodiment, the camera 6108 may be the same as or similar to thecamera 226. The camera 6108 may be capable of taking video, audio,photographs, and/or any combination of the three. In one embodiment, thecamera 6108 may be capable of resisting impacts, collisions, water,and/or may have a stabilization system to keep picture from blurringwhile the body 6112 is in motion. A lens of the camera 6108 may bescratch and/or impact resistant and/or proof. The camera 6108 may have amemory item (e.g., a memory card) associated with it. Informationcaptured by the camera (e.g., audio data, video data and/or pictorialdata) may be stored by the neighborhood flying football 6100A, thecommerce server 4200, and/or the data processing system 4204. In oneembodiment, the information captured by the camera may be capable ofbeing downloaded and/or uploaded via the USB port 6196.

In one embodiment, the USB port 6106 may be associated with the body6112 (e.g., located on the surface of the body 6112 and/or within thebody 6112). The USB port 6106 may be communicatively coupled with thecamera 6108 and/or a memory of the neighborhood flying football. The USBport 6106 may enable the user to access from and/or download data to theneighborhood flying football 6100A. The data may include, but is in noway limited to, audio data, video data, pictorial data, GPS relateddata, usage data, energy usage data, flight record data and/or recordedmessages (e.g., messages to and/or from other users). The USB port 6106may be capable of being used to charge (e.g., supply power to) theneighborhood flying football 6100A. In one embodiment, the USB port 6106may supply power to the power source 6104. The power source 6104 may bethe same as and/or similar to the energy source 212, the power supply258, and/or the batteries placed in the multiple battery compartments4306.

In one embodiment, the power source may be solar powered, harness powerfrom air resistance and/or air flow around (e.g., through grooves on thebody's 6112 surface) the neighborhood flying football 6100A, and/orgenerate power from the motion of the body 6112 when in motion (e.g.,from gyroscopic motion and/or rotating motion when the body 6112 isthrown). In one embodiment, the power supply 6104 may supply power tothe camera 6108. The neighborhood flying football 6100A may have anynumber of power sources 6104 and/or may use separate power sources 6104to power the propellers, camera, and/or any other system of theneighborhood flying football 6100A.

The storage compartment 6110 may be within the body 6112 and/or may becapable of being accessed from the exterior of the body 6112. Thestorage compartment may possess the capabilities and/or features of, bethe same as and/or similar to the detachable storage compartment 4301and/or storage compartment 101. The storage compartment 6110 may becapable of storing contents in such a way as to maintain a balanceand/or center of gravity of the body 6112 and/or neighborhood flyingfootball 6100A so as to enable the body 6112 to be used as a normalrecreational device (e.g., thrown and/or caught like a normal football)and/or to enable the neighborhood flying football 6100A to effectivelyand/or efficiently travel. In one embodiment, the power source 6104,storage compartment 6110 etc. may be capable of being removed and/orrearranged (e.g., if only the storage compartment 6110 is removed, theremaining elements may be rearranged) to achieve the above mentionedeffects. The storage compartment 6110, power source 6104, USB port 6106,camera 6108 and/or any other component of the body 6112 may be arrangedis a manner to provide balance, stability, and/or center of gravity toenable the body 6112 to be used as a normal recreational device (e.g.,thrown and/or caught like a normal football) and/or to enable theneighborhood flying football 6100A to effectively and/or efficientlytravel. In one embodiment, the neighborhood flying football 6100A may becapable of being controlled and/or communicatively coupled with the dataprocessing system 4204.

FIG. 61B is a view of a neighborhood flying football 6100B beingcontrolled by the data processing system 4204, according to oneembodiment. In one embodiment, the neighborhood flying football 6100Bmay be the same as the neighborhood flying football 6100B and/or possessthe same or similar components and/or capabilities. In one embodiment,the neighborhood flying football 6100B may have a rotor 6114 and set ofrotor blades 6116. The rotor 6114 and/or set of rotor blades 6116 may bearranged in a helicopter alignment.

In one embodiment, the neighborhood flying football 6100B may be able tobe controlled by the data processing system 4204. The data processingsystem 4204 may be communicatively coupled with the neighborhood flyingfootball 6100B and/or may be able to view and/or communicate theinformation and/or actions shown in FIGS. 53-54 and 57. In oneembodiment, the neighborhood flying football 6100B may keep flightrecords, usage records and/or flight recordings and/or communicate thedata to the data processing system 4204. The data processing system 4204may display the images captured by the camera 6108. In one embodiment,the camera 6108 may be capable of being moved, rotated, zoom in and/orout etc. In one embodiment, the body 6112 may be designed to protect thecamera 6108, USB port 6106 etc. from damage caused by impact, water,etc. The body 6112 may have a shape so as to allow the neighborhoodflying football 6100B to land safely and stably. The body 6112 may havedetachable and/or retractable landing mechanisms (e.g., legs, landingplatform(s), and/or gears) to enable the neighborhood flying football6100B to fly, hover, and/or land effectively.

People in suburbia and urban cities now may not even know who theirneighbors are. Communities have become more insular. There may be a fewactive people in each neighborhood who know about their neighborhood andare willing to share what they know with others. They should be able toshare this information with others through the Internet. Many peoplewant to know who their neighbors are and express themselves and theirfamilies through the internet. People want to also know aboutrecommendations and what kind of civic and cultural things are in theneighborhood. What is contemplated includes: A social network for peoplewho want to get to know their neighbors and/or neighborhoods.Particularly, one in which a set of maps of neighborhoods (e.g., such asthose on Zillow.com or provided through Google® or Microsoft®) are usedas a basis on which a user can identify themselves with a particularaddress. This address may be verified through one or more of the moduleson FIG. 29. Particularly, this address may be the current address of theuser is living, a previous address where the user used to live, etc.

The address may be verified through a credit check of the user, or acopy of the user's drivers license. Once the user is approved in aparticular home/location, the user can leave their comments about theirhome. They can mark their home information proprietary, so that no oneelse can contribute to their info without their permission. They canhave separate private and public sections, in which the private sectionis shared with only verified addresses of neighbors, and the publicsection is shared with anybody viewing their profile. The user can thencreate separate social networking pages for homes, churches, locations,etc. surrounding his verified address. As such, the user can expresshim/herself through their profile, and contribute information about whatthey're neighborhood is like and who lives there. Only verifiedindividuals or entities might be able to view information in thatneighborhood.

The more information the user contributes, the higher his or her statuswill be in the neighborhood through a marker (e.g., a number of stars),or through additional services offered to the neighbor, such as theability to search a profiles of neighbors in a larger distance rangefrom a verified address of the user. For example, initially, the usermay only be able to search profiles within 1 mile on their principal,current home after being verified as living in there. When they create aprofiles for themselves and/or contribute profiles of other people, theymay widen their net of private profiles they may be allowed to search(e.g., because they become a trusted party in the neighborhood byoffering civic information). Neighbors can leave feedback for eachother, and arrange private block parties, etc. through their privateprofile. All these features may possible through one or more of theembodiments and/or modules illustrated in FIGS. 1A-61B. Through theirpublic profile, neighbors can know if there is a doctor living down thestreet, or an attorney around the corner. The FIGS. 1A-61B illustratevarious embodiments that may be realized. While a description is givenhere, a self-evident description can be derived for the software andvarious methods, software, and hardware directly from the attachedFigures.

A neighborhood expression and user contribution system is disclosed. Inone aspect, the technology allows users to see the value of millions ofhomes across the United States and/or the world, not just those that theuser themselves own or live in, because they can share information abouttheir neighbors. People living in apartments or condos can use theapartment/condo modeler wizard (e.g., as illustrated in FIG. 29) tocreate models (e.g. 2 or 3d) of their building and share informationabout their apartment/home and of their neighbors with others. Thetechnology has an integrated targeted advertising system for enablingadvertisers to make money through the social community module 2900 bydelivering targeted and non-targeted advertisements.

Aside from giving user generated content of information of homes, thesystem may also provide value estimates of homes it may also offersseveral unique features including value changes of each home in a giventime frame (e.g. 1, 5, or 10 years) and aerial views of homes as well asthe price of the surrounding homes in the area. It may also providesbasic data of a given home such as square footage and the number ofbedrooms and bathrooms. Users may can also obtain current estimates ofhomes if there was a significant change made such as recently modeledkitchen.

In the example systems and methods illustrated in FIGS. 1A-61B,neighbors may get to know each other and their surrounding businessesmore easily through the Internet. The user interface view of the socialcommunity module may include a searchable map interface and/or a socialnetworking page on the right when one clicks a particular home/location.The map interface may/may not include information about prices of ahome, or information about the number of bedrooms of a home, etc. Inessence, certain critical input information may be divided as follows:

Residential location: (1) name of the persons/family living in thatresidence (2) Their profession if any 3) Their educational background ifany (4) Their recreational interests (5) About their family descriptionbox (6) Anything else people want to post about that person includingtheir interests, hobbies, etc. (7) An ability for users to leaveendorsements.

Business location or civic location (e.g., park, govt. building, church,etc.): (1) name of the business/location (2) email of the manager of thebusiness/location (3) phone number of the business/location if known (4)anything else people want to say about the business (good or bad), forexample, contributable through a claimable.

These two will be the primary types. Various features differentiateexample embodiments of the social community module from other socialnetworks. These differentiators include (1) interface driven by address(2) maps that can be viewed, zoomed in on, tied to a parcel #, etc. (3)Anyone can populate anyone's social network page. (4) Anybody can postin one of the boxes. They can post anonymously or publicly (5) Ifsomeone wants to override information that already has been established,they will need to have an identity (e.g., user name), to overridepublished posting information.

However, according to one embodiment, if an owner of an entity locationwishes to mark their location private, and uneditable by the publicwithout their permission, they will need to pay (e.g., a monthly fixedfee) through the social community module. Alternatively, the owner ofthe entity location may not need to pay to mark the location as privateand uneditable by the public without the owner's permission. Exampleembodiments of the social community module may feature info aboutbusinesses. They may also feature info about people that live in thehomes, and may/may not display information on prices, number ofbedrooms, etc.

The social community module (e.g., as described in FIG. 29) may be asearch engine (e.g., Google®, Yahoo®, etc.) that uses maps (e.g.,satellite map views) instead of text displays to show information, userprofiles, reviews, promotions, ads, directions, events, etc. relevant touser searches.

The example systems and methods illustrated in FIGS. 1A-61B mayfacilitate a social network membership that spreads virally by usersinviting their friends. For example, every person that registers hastheir own profile, but registration may not be required to contributecontent. However, registration may be required to “own” content on yourown home, and have override permission to delete things that you don'tlike about yourself listed about you by others. In one embodiment, thesocial community module may need to confirm the user's identity andaddress (e.g., using digital signature tools, drivers licenseverification, etc.), and/or the user may need to pay a monthly fixed fee(e.g., through a credit card) to control their identity.

For example, they can get a rebate, and not have to pay the monthly feefor a particular month, if they invite at least 15 people that month ANDcontribute information about at least 10 of their neighbors, friends,civic, or business locations in their neighborhood. People can post picsof their family, their business, their home, etc. on their profile oncethey ‘own’ their home and register. In another embodiment, endorsementsfor neighbors by others will be published automatically. People cansearch for other people by descriptors (e.g., name, profession, distanceaway from me, etc.)

Profiles of users may be created and/or generated on the fly, e.g., whenone clicks on a home.

People may be able to visually see directions to their neighborhoodbusinesses, rather than reading directions through text in a firstphase. After time, directions (e.g., routes) can be offered as well.Users can leave their opinions on businesses, but the social communitymodule also enables users to leave opinions on neighbors, occupants orany entity having a profile on the map display. The social communitymodule may not attempt to restrict freedom of speech by the users, butmay voluntarily delete slanderous, libelous information on the requestof an owner manually at any time.

In one embodiment, the methods and systems illustrated in FIGS. 1A-61Benable people to search for things they want e.g. nearby pizzas etc.(e.g., by distance away). Advertisers can ‘own’ their listing by placinga display ad on nextdoor.com. Instead of click-through revenues whensomeone leaves the site, revenues will be realized when the link isclicked and someone views a preview html on the right of the visual map.Targeted advertisements may also be placed when someone searches aparticular street, name, city, etc.

In another example embodiment, the social community module may enableusers of the social network to populate profiles for apartments,buildings, condos, etc. People can create floors, layout, etc. of theirbuilding, and add social network pages on the fly when they click on alocation that has multiple residents, tenants, or lessees.

A user interface associated with the social community module 2900 may beclean, simple, and uncluttered (e.g., Simple message of “get to knowyour neighbors”). For example, the map interface shows neighbors.Methods and systems associated with the features described may focus onuser experience, e.g., ensuring a compelling message to invite friendsand/or others to join. A seed phase for implementation of the methodsand systems illustrated in FIGS. 1A-61B may be identified for building amembership associated with the social community module.

For example, a user having extensive networks in a certain area (e.g., acity) may seed those communities as well. The social network mayencourage user expression, user content creation, ease of use on site toget maximum users/distribution as quickly as possible. In anotherembodiment, the social community module may ensure that infrastructureassociated with operation of the social community module (e.g., servers)are able to handle load (e.g., data traffic) and keep up with expectedgrowth.

For example, the user interface view illustrated in the various figuresshows an example embodiment of the social community module of FIG. 29.The user interface view may include a publicly editable profile wallsection allowing public postings that owners of the profile can edit.For example, any user may be able to post on an empty profile wall, buta user must claim the location to own the profile (e.g., may minimizebarriers to users posting comments on profile walls).

Names featured on the profile wall may be links to the user profiles onthe map (e.g., giving an immediate sense for the location of admirers(or detractors) relative to user location). In one embodiment, an action(e.g., mouse-over) on a comment would highlight the comment user's houseon the map and names linking to user profiles. The user interface viewmay also utilize the mapping interface to link comments to locations.

For example, the various embodiments illustrate a comment announcing agarage sale, that is tied to a mappable location on the mappinginterface. (e.g., allows people to browse references directly frompeople's profiles.). In the various figures, an example display of themapping interface is illustrated. In this example display, houses areshown in green, a church is shown in white, the red house shows theselected location and/or the profile owner's house, question marksindicate locations without profile owners, blue buildings are commerciallocations, and the pink building represents an apartment complex.

Houses with stars indicate people associated with (e.g., “friends”) ofthe current user. In one embodiment, a user action (e.g., mouse-over) ona commercial property displayed in the mapping interface may pull up astar (e.g., “***) rating based on user reviews, and/or a link to theprofile for the property. A mouse-over action on the apartment complexmay pull up a building schematic for the complex with floor plans, onwhich the user can see friends/profiles for various floors or rooms.Question marks indicated in the display may prompt users to own thatprofile or post comments on the wall for that space. A user action onany house displayed in the mapping interface may pull up a profile link,summary info such as status, profession, interests, etc. associated withthe profile owner, a link to add the person as a friend, and/or a linkto send a message to the user (e.g., the profile owner).

In another embodiment, a default profile view shown is that of thecurrent user (e.g., logged in), and if the user clicks on any otherprofile, it may show their profile in that space instead (with few textchanges to indicate different person). The events in your area view ofthe profile display in may have a default radius for notification ofevents (e.g., by street, by block, by neighborhood, county, etc.) Eventsare associated with user profiles and may link to locations displayed onthe mapping interfaces. The hot picks section may be an ad/promotionalzone, with default settings for radius of alerts also configurable.

For example, the “Find a Friend” section may permit users to search byname, address, interests, status, profession, favorite movies/music/foodetc. Users are also able to search within a given radius of theirlocation. In one embodiment, the user interface view may include a linkfor the user to invite other people to join the network (e.g., mayencourage users who see a question-mark on a house or a location on themapping interface that corresponds to a real location associated withsomeone they know to contact that person and encourage them to join andown that profile through the social community module).

Some of the reasons we believe these embodiments are unique include:

Search engine that provides a visual map (e.g., rather than text)display of information relevant to user queries.

Users can search on the map for other people having certainprofessional, educational, personal, extracurricular, cultural,political and/or family etc. profiles or interests, within any locationrange.

Users can search for information on the map, that is accessible directlythrough profile displays. For example, the user may search forinformation about a certain subject and be directed to a profile ofanother user having information about the subject. Alternatively, theuser may view the search subject itself as a visible item (e.g., ifapplicable to the search query) having a profile on the map display,along with additional information associated with the item (e.g.,contributed by other users).

Allows users to search, browse and view information posted by otherusers about an entity location such as a home, a business property, acondo, an apartment complex, etc. directly on a map display.

Allows users to browse, form and join groups and communities based onlocation, preferences, interests, friend requests, etc.

Users can send messages to other people through their profiles withinthe map display.

Users can find friends, business associates, vendors, romantic partners,etc. on the map within any location range (e.g., in their neighborhood,street, subdivision, etc.) by browsing the map display or searching forpeople with certain profile characteristics and/or similar interests.

Users can view, browse and post comments/information/reviews aboutentity locations and/or people associated with those locations (e.g.,occupants of a house, families, apartment residents, businesses,non-governmental entities, etc.), even for locations that do not have aprofile owner. For example, all entity locations visible on the mapdisplay may link to a profiles on which any user can post comments. Toown the profile and edit the information posted about an entity locationor the occupant(s), the occupant(s) would have to join the networkassociated with the social community module and become the owner of theprofile. The profile owner would then become visible in the map display(e.g., entity locations without profile owners may only be visible asquestions marks on the map, having blank profiles but public commentsections).

Users can share their comments and opinions about locations, preferencesand/or interests on their profiles that are visible and searchable onthe map display

Automatically notifies users of events and promotions in an area (e.g.,scope of area can be selected by the user), and highlights venues anduser profiles on the map.

Users can post reviews about entity locations (e.g., businesses) suchthat ratings for entity locations are visible on the map. Other userscan trace the location of the users that posted the comments on the map.

Users who post comments on other profiles can be traced directly on themap through their comments. Alternatively, users can choose to submitanonymous postings or comments on other user/entity profiles, and/or maychoose not to be traceable on the map through their comments.

For entity locations having more than one residency unit (e.g.,apartment complexes), people can create and post on profiles for anyroom/floor of the location (e.g., by entering information on a schematicview of the location that is visible on the map).

Users can visually determine routes/directions/orientation to locationsthat they can browse within the map display. Additionally, users cangenerate written driving, walking or public transit directions betweenpoints of interest (e.g., from the user's house to a friend's house)within the map display.

Users can communicate (e.g., through live chat) directly with otherusers in the area based on an association determined through theirprofiles

Business entity locations can generate targeted ads and promotionswithin locations on the map display (e.g., virtual billboards).

The social community module can realize revenue based on adclickthroughs by users, without the users being directed away from theinterface. For example, when a user clicks on any targeted ad/promotiondisplayed on the map, the profile of the entity associated with thead/promotion may be generated alongside the map display.

Neighborhood or neighborhood (see spelling differences) is ageographically localized community located within a larger city orsuburb. The residents of a given neighborhood are called neighbors (orneighbors), although this term may also be used across much largerdistances in rural areas.

Traditionally, a neighborhood is small enough that the neighbors are allable to know each other. However in practice, neighbors may not know oneanother very well at all. Villages aren't divided into neighborhoods,because they are already small enough that the villagers can all knoweach other.

The system however may work in any country and any geography of theworld. In Canada and the United States, neighborhoods are often givenofficial or semi-official status through neighborhood associations,neighborhood watches, or block watches. These may regulate such mattersas lawn care and fence height, and they may provide such services asblock parties, neighborhood parks, and community security. In some otherplaces the equivalent organization is the parish, though a parish mayhave several neighborhoods within it depending on the area.

In localities where neighborhoods do not have an official status,questions can arise as to where one neighborhood begins and anotherends, such as in the city of Philadelphia, Pa. Many cities may usedistricts and wards as official divisions of the city, rather thantraditional neighborhood boundaries.

In the mainland of the People's Republic of China, the term is generallyused for the urban administrative unit usually found immediately belowthe district level, although an intermediate, sub-district level existsin some cities. They are also called streets (administrative terminologymay vary from city to city). Neighborhoods encompass 2,000 to 10,000families. Within neighborhoods, families are grouped into smallerresidential units or quarters of 2900 to 3400 families and supervised bya residents' committee; these are subdivided into residents' smallgroups of fifteen to forty families. In most urban areas of China,neighborhood, community, residential community, residential unit,residential quarter have the same meaning:

or

or

or

, and is the direct sublevel of a subdistrict (

), which is the direct sublevel of a district (

), which is the direct sublevel of a city (

). (See Political divisions of China.

The system and methods may be distributed through neighborhoodassociations. A neighborhood or neighborhood (see spelling differences)is a geographically localized community located within a larger city orsuburb. The residents of a given neighborhood are called neighbors (orneighbors), although this term may also be used across much largerdistances in rural areas.

Traditionally, a neighborhood is small enough that the neighbors are allable to know each other. However in practice, neighbors may not know oneanother very well at all. Villages aren't divided into neighborhoods,because they are already small enough that the villagers can all knoweach other. Each of the technologies and concepts disclosed herein maybe embodied in software and/or hardware through one or more of themodules/embodiments discussed in FIGS. 1A-61B.

A block party is a large public celebration in which many members of asingle neighborhood congregate to observe a positive event of someimportance. Many times, there will be celebration in the form of playingmusic and dance. Block parties gained popularity in the United Statesduring the 1970s. Block Parties were often held outdoors and power forthe DJ's sound system was taken illegally from street lights. This wasfamously referenced in the song “South Bronx” by KRS-One with the line:

“Power from a street light made the place dark. But yo, they didn'tcare, they turned it out.” It is also interesting to note that manyinner city block parties were actually held illegally, as they might bedescribed as loitering. However, police turned a blind eye to them,reasoning that if everyone from the neighborhood was gathered in oneplace there was less chance of crime being committed elsewhere.

In the suburbs, block parties are commonly held on holidays such asFourth of July or Labor Day. Sometimes the occasion may be a theme sucha “Welcome to the Neighborhood” for a new family or a recent popularmovie. Often block parties involve barbecuing, lawn games such as SimonSays and group dancing such as the Electric Slide, the Macarena or linedancing.

In other usage, a block party has come to mean any informal publiccelebration. For example, a block party can be conducted via televisioneven though there is no real block in the observance. The same is truefor the Internet. The block party is closely related to the beach party.The British equivalent is the street party.

The systems and methods illustrated in FIGS. 1A-61B may have software toemulate a block party or a neighborhood watch. A neighborhood watch(also called a crime watch or neighborhood crime watch) is a citizens'organization devoted to crime and vandalism prevention within aneighborhood. It is not a vigilante organization, since members areexpected not to directly intervene in possible criminal activity.Instead, neighborhood watch members are to stay alert to unusualactivity and contact the authorities. It builds on the concept of a townwatch from Colonial America.

The current American system of neighborhood watches began developing inthe late 1960s as a response to the rape and murder of Kitty Genovese inQueens, N.Y. People became outraged that three dozen witnesses didnothing to save Genovese or to apprehend her killer Some locals formedgroups to watch over their neighborhoods and to look out for anysuspicious activity in their areas. Shortly thereafter, the NationalSheriffs' Association began a concerted effort in 1972 to revitalize the“watch group” effort nationwide.

A neighborhood watch (also called a crime watch or neighborhood crimewatch) is a citizens' organization devoted to crime and vandalismprevention within a neighborhood. It is not a vigilante organization,since members are expected not to directly intervene in possiblecriminal activity. Instead, neighborhood watch members are to stay alertto unusual activity and contact the authorities. It builds on theconcept of a town watch from Colonial America.

The current American system of neighborhood watches began developing inthe late 1960s as a response to the rape and murder of Kitty Genovese inQueens, N.Y. People became outraged that three dozen witnesses didnothing to save Genovese or to apprehend her killer Some locals formedgroups to watch over their neighborhoods and to look out for anysuspicious activity in their areas. Shortly thereafter, the NationalSheriffs' Association began a concerted effort in 1972 to revitalize the“watch group” effort nationwide.

The various methods, systems, and apparatuses disclosed herein andillustrated and described using the attached FIGS. 1A-61B can be appliedto creating online community organizations of neighborhoods of any form.During human growth and maturation, people encounter sets of otherindividuals and experiences. Infants encounter first, their immediatefamily, then extended family, and then local community (such as schooland work). They thus develop individual and group identity throughassociations that connect them to life-long community experiences.

As people grow, they learn about and form perceptions of socialstructures. During this progression, they form personal and culturalvalues, a world view and attitudes toward the larger society. Gaining anunderstanding of group dynamics and how to “fit in” is part ofsocialization. Individuals develop interpersonal relationships and beginto make choices about whom to associate with and under whatcircumstances.

During adolescence and adulthood, the individual tends to develop a moresophisticated identity, often taking on a role as a leader or followerin groups. If associated individuals develop the intent to give ofthemselves, and commit to the collective well-being of the group, theybegin to acquire a sense of community.

Socialization: The process of learning to adopt the behavior patterns ofthe community is called socialization. The most fertile time ofsocialization is usually the early stages of life, during whichindividuals develop the skills and knowledge and learn the rolesnecessary to function within their culture and social environment. Forsome psychologists, especially those in the psychodynamic tradition, themost important period of socialization is between the ages of 1 and 10.But socialization also includes adults moving into a significantlydifferent environment, where they must learn a new set of behaviors.

Socialization is influenced primarily by the family, through whichchildren first learn community norms. Other important influences includeschool, peer groups, mass media, the workplace and government. Thedegree to which the norms of a particular society or community areadopted determines one's willingness to engage with others. The norms oftolerance, reciprocity and trust are important “habits of the heart,” asde Tocqueville put it, in an individual's involvement in community.

Continuity of the connections between leaders, between leaders andfollowers, and among followers is vital to the strength of a community.Members individually hold the collective personality of the whole. Withsustained connections and continued conversations, participants incommunities develop emotional bonds, intellectual pathways, enhancedlinguistic abilities, and even a higher capacity for critical thinkingand problem-solving. It could be argued that successive and sustainedcontact with other people might help to remove some of the tension ofisolation, due to alienation, thus opening creative avenues that wouldhave otherwise remained impassable.

Conversely, sustained involvement in tight communities may tend toincrease tension in some people. However, in many cases, it is easyenough to distance oneself from the “hive” temporarily to ease thisstress. Psychological maturity and effective communication skills arethought to be a function of this ability. In nearly every context,individual and collective behaviors are required to find a balancebetween inclusion and exclusion; for the individual, a matter of choice;for the group, a matter of charter. The sum of the creative energy(often referred to as “synergy”) and the strength of the mechanisms thatmaintain this balance is manifest as an observable and resilient senseof community.

McMillan and Chavis (1986) identify four elements of “sense ofcommunity”: 1) membership, 2) influence, 3) integration and fulfillmentof needs, and 4) shared emotional connection. They give the followingexample of the interplay between these factors: Someone puts anannouncement on the dormitory bulletin board about the formation of anintramural dormitory basketball team. People attend the organizationalmeeting as strangers out of their individual needs (integration andfulfillment of needs). The team is bound by place of residence(membership boundaries are set) and spends time together in practice(the contact hypothesis). They play a game and win (successful sharedvalent event). While playing, members exert energy on behalf of the team(personal investment in the group). As the team continues to win, teammembers become recognized and congratulated (gaining honor and statusfor being members). Someone suggests that they all buy matching shirtsand shoes (common symbols) and they do so (influence).

A Sense of Community Index (SCI) has been developed by Chavis and hiscolleagues (1986). Although originally designed to assess sense ofcommunity in neighborhoods, the index has been adapted for use inschools, the workplace and a variety of types of communities.

Communitarianism as a group of related but distinct philosophies (orideologies) began in the late 20th century, opposing classicalliberalism, capitalism and socialism while advocating phenomena such ascivil society. Not necessarily hostile to social liberalism,communitarianism rather has a different emphasis, shifting the focus ofinterest toward communities and societies and away from the individual.The question of priority, whether for the individual or community, mustbe determined in dealing with pressing ethical questions about a varietyof social issues, such as health care, abortion, multiculturalism, andhate speech.

Effective communication practices in group and organizational settingsare important to the formation and maintenance of communities. How ideasand values are communicated within communities are important to theinduction of new members, the formulation of agendas, the selection ofleaders and many other aspects. Organizational communication is thestudy of how people communicate within an organizational context and theinfluences and interactions within organizational structures. Groupmembers depend on the flow of communication to establish their ownidentity within these structures and learn to function in the groupsetting. Although organizational communication, as a field of study, isusually geared toward companies and business groups, these may also beseen as communities. The principles can also be applied to other typesof communities.

If the sense of community exists, both freedom and security exist aswell. The community then takes on a life of its own, as people becomefree enough to share and secure enough to get along. The sense ofconnectedness and formation of social networks comprise what has becomeknown as social capital.

Azadi Tower is a town square in modern Iran. Social capital is definedby Robert D. Putnam as “the collective value of all social networks (whopeople know) and the inclinations that arise from these networks to dothings for each other (norms of reciprocity).” Social capital in actioncan be seen in groups of varying formality, including neighbors keepingan eye on each others' homes. However, as Putnam notes in Bowling Alone:The Collapse and Revival of American Community (30000), social capitalhas been falling in the United States. Putnam found that over the past25 years, attendance at club meetings has fallen 58 percent, familydinners are down 33 percent, and having friends visit has fallen 45percent.

Western cultures are thus said to be losing the spirit of community thatonce were found in institutions including churches and community centers2921. Sociologist Ray Oldenburg states in The Great Good Place thatpeople need three places: 1) The home, 2) the workplace, and, 3) thecommunity hangout or gathering place.

With this philosophy in mind, many grassroots efforts such as TheProject for Public Spaces are being started to create this “Third Place”in communities. They are taking form in independent bookstores,coffeehouses, local pubs and through many innovative means to create thesocial capital needed to foster the sense and spirit of community.

Community development is often formally conducted by universities orgovernment agencies to improve the social well-being of local, regionaland, sometimes, national communities. Less formal efforts, calledcommunity building or community organizing, seek to empower individualsand groups of people by providing them with the skills they need toeffect change in their own communities. These skills often assist inbuilding political power through the formation of large social groupsworking for a common agenda. Community development practitioners mustunderstand both how to work with individuals and how to affectcommunities' positions within the context of larger social institutions.

Formal programs conducted by universities are often used to build aknowledge base to drive curricula in sociology and community studies.The General Social Survey from the National Opinion Research Center atthe University of Chicago and the Saguaro Seminar at the John F. KennedySchool of Government at Harvard University are examples of nationalcommunity development in the United States. In The United Kingdom,Oxford University has led in providing extensive research in the fieldthrough its Community Development Journal, used worldwide bysociologists and community development practitioners.

At the intersection between community development and community buildingare a number of programs and organizations with community developmenttools. One example of this is the program of the Asset Based CommunityDevelopment Institute of Northwestern University. The institute makesavailable downloadable tools to assess community assets and makeconnections between non-profit groups and other organizations that canhelp in community building. The Institute focuses on helping communitiesdevelop by “mobilizing neighborhood assets”—building from the inside outrather than the outside in.

\Community building and organizing: M. Scott Peck is of the view thatthe almost accidental sense of community which exists at times ofcrisis, for example in New York City after the attacks of Sep. 11, 2001,can be consciously built. Peck believes that the process of “consciouscommunity building” is a process of building a shared story, andconsensual decision making, built upon respect for all individuals andinclusivity of difference. He is of the belief that this process goesthrough four stages:

Pseudo-community: Where participants are “nice with each other”,playing-safe, and presenting what they feel is the most favorable sidesof their personalities. Chaos: When people move beyond theinauthenticity of pseudo-community and feel safe enough to present their“shadow” selves. This stage places great demands upon the facilitatorfor greater leadership and organization, but Peck believes that“organizations are not communities”, and this pressure should beresisted.

Emptying: This stage moves beyond the attempts to fix, heal and convertof the chaos stage, when all people become capable of acknowledgingtheir own woundedness and brokenness, common to us all as human beings.Out of this emptying comes

Authentic community: the process of deep respect and true listening forthe needs of the other people in this community. This stage Peckbelieves can only be described as “glory” and reflects a deep yearningin every human soul for compassionate understanding from one's fellows.

More recently Scott Peck has remarked that building a sense of communityis easy. It is maintaining this sense of community that is difficult inthe modern world. The Ithaca Hour is an example of community-basedcurrency. Community building can use a wide variety of practices,ranging from simple events such as potlucks and small book clubs tolarger-scale efforts such as mass festivals and construction projectsthat involve local participants rather than outside contractors. Somecommunities have developed their own “Local Exchange Trading Systems”(LETS) and local currencies, such as the Ithaca Hours system, toencourage economic growth and an enhanced sense of community.

Community building that is geared toward activism is usually termed“community organizing.” In these cases, organized community groups seekaccountability from elected officials and increased directrepresentation within decision-making bodies. Where good-faithnegotiations fail, these constituency-led organizations seek to pressurethe decision-makers through a variety of means, including picketing,boycotting, sit-ins, petitioning, and electoral politics. The ARISEDetroit! coalition and the Toronto Public Space Committee are examplesof activist networks committed to shielding local communities fromgovernment and corporate domination and inordinate influence.

Community organizing is sometimes focused on more than just resolvingspecific issues. Organizing often means building a widely accessiblepower structure, often with the end goal of distributing power equallythroughout the community. Community organizers generally seek to buildgroups that are open and democratic in governance. Such groupsfacilitate and encourage consensus decision-making with a focus on thegeneral health of the community rather than a specific interest group.

The three basic types of community organizing are grassroots organizing,coalition building, and faith-based community organizing (also called“institution-based community organizing,” “broad-based communityorganizing” or “congregation-based community organizing”).

Community service is usually performed in connection with a nonprofitorganization, but it may also be undertaken under the auspices ofgovernment, one or more businesses, or by individuals. It is typicallyunpaid and voluntary. However, it can be part of alternative sentencingapproaches in a justice system and it can be required by educationalinstitutions.

The most common usage of the word “community” indicates a large groupliving in close proximity. Examples of local community include: Amunicipality is an administrative local area generally composed of aclearly defined territory and commonly referring to a town or village.Although large cities are also municipalities, they are often thought ofas a collection of communities, due to their diversity.

A neighborhood is a geographically localized community, often within alarger city or suburb. A planned community is one that was designed fromscratch and grew up more or less following the plan. Several of theworld's capital cities are planned cities, notably Washington, D.C., inthe United States, Canberra in Australia, and Brasilia in Brazil. It wasalso common during the European colonization of the Americas to buildaccording to a plan either on fresh ground or on the ruins of earlierAmerindian cities. Identity: In some contexts, “community” indicates agroup of people with a common identity other than location. Membersoften interact regularly. Common examples in everyday usage include: A“professional community” is a group of people with the same or relatedoccupations. Some of those members may join a professional society,making a more defined and formalized group.

These are also sometimes known as communities of practice. A virtualcommunity is a group of people primarily or initially communicating orinteracting with each other by means of information technologies,typically over the Internet, rather than in person. These may be eithercommunities of interest, practice or communion. (See below.) Researchinterest is evolving in the motivations for contributing to onlinecommunities.

Some communities share both location and other attributes. Memberschoose to live near each other because of one or more common interests.A retirement community is designated and at least usually designed forretirees and seniors—often restricted to those over a certain age, suchas 55. It differs from a retirement home, which is a single building orsmall complex, by having a number of autonomous households.

An intentional community is a deliberate residential community with amuch higher degree of social interaction than other communities. Themembers of an intentional community typically hold a common social,political or spiritual vision and share responsibilities and resources.Intentional communities include Amish villages, ashrams, cohousing,communes, ecovillages, housing cooperatives, kibbutzim, and land trusts.

Special nature of human community Music in Central Park, a public space.Definitions of community as “organisms inhabiting a common environmentand interacting with one another,” while scientifically accurate, do notconvey the richness, diversity and complexity of human communities.Their classification, likewise is almost never precise. Untidy as it maybe, community is vital for humans. M. Scott Peck expresses this in thefollowing way: “There can be no vulnerability without risk; there can beno community without vulnerability; there can be no peace, andultimately no life, without community.” This conveys some of thedistinctiveness of human community.

Embodiments described herein in FIGS. 14-41B govern a new kind of socialnetwork for neighborhoods, according to one embodiment (e.g., may beprivate and/or wiki-editable search engine based). It should be notedthat in some embodiments, the address of an user may be masked from thepublic search (but still may be used for privacy considerations),according to one embodiment. Some embodiments have no preseeded data,whereas others might. Embodiments described herein may present rich,location specific information on individual residents and businesses.

A user can “Claim” one or more Business Pages and/or a ResidentialPages, according to one embodiment. In order to secure their Claim, theuser may verify their location associated with the Business Page and/orResidential page within 30 days, or the page becomes released to thecommunity, according to one embodiment. A user can only have a maximumof 3 unverified Claims out at any given time, according to oneembodiment. When a user clicks on “Claim this Page” on Business Profilepage and/or a Residential Profile page, they can indicate the manner inwhich they intend to verify their claim, according to one embodiment.Benefits of Claiming a Business Page and/or Residential page may enablethe user to mark their page ‘Self-Editable only’ from the default ‘FullyEditable’ status, and see “Private” listings in a claimed neighborhoodaround the verified location, according to one embodiment. Each edit bya user on a Residential Profile page and/or a Business Profile page maybe made visible on the profile page, along with a date stamp, accordingto one embodiment.

Browse function: Based on the user's current location, the browsefunction may display a local map populated with pushpins forlocation-specific information, and a news feed, made up of business pageedits, public people page edits, any recent broadcasts, etc., accordingto one embodiment. The news feed may show up on each Business Page andeach Residential Page, based on activity in the surrounding area,according to one embodiment. Secure a Neighborhood function: May allowthe user to identify and “secure” a neighborhood, restricting certaintypes of access to verified residents, according to one embodiment. Adda Pushpin function: May allow any registered or verified user to add anytype of Pushpin (as described in FIG. 36), to one embodiment.

In addition to the map, the search results page may display a news feed,made up of business page edits, public people page edits, any recentbroadcasts, and autogenerated alerts who has moved into theneighborhood, who has moved out of the neighborhood, any recent reviewsin the neighborhood, any pushpins placed in the immediate area, etc.,according to one embodiment. The news feed may prioritize entriesrelating to the search results, and will take into account privacypolicies and preferences, according to one embodiment.

Example Newsfeeds may include:

Joe Smith moved into the neighborhood in September 2013. Welcome Joe!Like Share; 43 neighbors (hyperlink) moved in to the Cupertino libraryneighborhood in July 2013. Like Share; 12 neighbors (hyperlink) verifiedin to the Cupertino library neighborhood in July 2013. Like Share; RajAbhyanker invited Paul Smith, a guest to the Cupertino neighborhood. Rajindicates Paul is a friend from college looking to move into theneighborhood. Welcome Paul!: Raj Abhvanker posted a Nissan Leaf for rent$35 a day, in mountain view Rent now. Like Share

This content may feed each Profile Page and helps to increase SearchEngine value for content on the site, according to one embodiment.Alerts may be created and curated (prioritized, filtered) automaticallyand/or through crowdsourcing, to keep each page vibrant and activelyupdating on a regular basis (ideally once a day or more), according toone embodiment.

A Multi-Family Residence page will display a list of residents in theentire building, according to one embodiment. Clicking on any residentwill display a Single Family Residence page corresponding to theindividual living unit where that person resides, according to oneembodiment.

For example, suppose that John Smith and Jane Smith live in apartment 12of a large building. Their names are included in the list of residents.When a user clicks on either John Smith or Jane Smith, we will display a“Single Family Residence” page showing both John and Jane, just as ifapartment 12 was a separate structure, according to one embodiment.

The broadcast feature (e.g., associated with the neighborhood broadcastdata and generated by the Bezier curve algorithm 3040 of the socialcommunity module 2906) may be a “Radio” like function that uses themobile device's current geospatial location to send out information toneighbors around the present geospatial location of the user, accordingto one embodiment. Broadcasts may be posted to neighbor pages in thegeospatial vicinity (e.g., in the same neighborhood) on public andprivate pages in the geospatial social network, according to oneembodiment. These broadcasts may enable any user, whether they live in aneighborhood or not to communicate their thoughts to those that live orwork (or have claimed) a profile in the neighborhood around where thebroadcaster is physically at, regardless of where the broadcaster lives,according to one embodiment. Broadcasts can be audio, video, pictures,and or text, according to one embodiment. For accountability, thebroadcaster may be a verified user and their identity made public to allusers who receive the broadcast in one embodiment.

This means that the broadcast feature may be restricted to be used onlyby devices (e.g., mobile phones) that have a GPS chip (or othergeolocation device) that an identify a present location of where thebroadcast is originating from, according to one embodiment. Thebroadcast may be sent to all users who have claimed a profile in the geospatial vicinity where the broadcast originates, according to oneembodiment. This can either be broadcast live to whoever is “tuned” into a broadcast of video, audio, picture, and text in their neighborhood,or can be posted on each users profile if they do not hear the broadcastto the neighborhood in a live mode in one embodiment.

When a broadcast is made neighbors, around where the broadcast is made,they may receive a message that says something like:

Raj Abhyanker, a user in Menlo Park just broadcast “Japanese culturalprogram” video from the Cupertino Union church just now. Watch, Listen,View

This broadcast may be shared with neighbors around Menlo park, and or inCupertino. This way, Raj's neighbors and those in Cupertino can knowwhat is happening in their neighborhoods, according to one embodiment.In one embodiment, the broadcast only goes to one area (Cupertino orMenlo park in the example above).

Broadcasts could be constrained to devices that have geospatial accuracyof present location and a current only (mobile devices for example).Otherwise, broadcasts won't mean much, according to one embodiment(would otherwise be just like thoughts/video upload without this).Broadcasts shouldn't be confused with ‘upload videos’, according to oneembodiment. Different concepts. Why? Broadcasts have an accuracy of timeand location that cannot be altered by a user, according to oneembodiment, Hence, mobile is the most likely medium for this not desktopcomputer, according to one embodiment. We should not let the user settheir own location for broadcasts (like other pushpin types), accordingto one embodiment. Also time is fixed, according to one embodiment.Fixing and not making these two variables editable give users confidencethat the broadcast was associated with a particular time and place, andcreates a very unique feature, according to one embodiment. For example,it would be not useful if the broadcast is untrusted as to location oforigination, according to one embodiment. E.g., I broadcast when I amsomewhere only about the location I am at, according to one embodiment.

Broadcasts are different that other pushpins because location of where abroadcast, and time of broadcast is *current location* and *currenttime*, according to one embodiment. They are initiated wherever abroadcaster is presently at, and added to the news feed in thebroadcasters neighborhood and in the area wherever a broadcaster ispresently at, according to one embodiment.

Broadcast rules may include:

1. If I post a Broadcast in my secured neighborhood, only my neighborscan see it, according to one embodiment.

2. If I post a Broadcast in different secured neighborhood then my own,my neighbors can see it (e.g., unless I turn this off in my privacysetting) and neighbors in the secured neighborhood can see it (e.g.,default not turn-offable, but I can delete my broadcast), according toone embodiment.

3. If I post a Broadcast in different unsecured neighborhood then myown, my neighbors can see it (unless I turn this off in my privacysetting) and the broadcast is publicly visible on user pages of publicuser profiles in the unsecured neighborhood until profiles are claimedand/or the neighborhood is secured, according to one embodiment.

4. If an outsider in a secure neighborhood posts a broadcast in mysecure neighborhood, it's not public, according to one embodiment.

5. If an outsider in a unsecure neighborhood posts a broadcast in mysecure neighborhood, the system does not post on profiles in hisunsecure neighborhood (to prevent stalking, burglary), but does post inmy secure neighborhood, according to one embodiment.

Privacy settings. For each verified residential or business location,the user may set Privacy to Default, Public, Private, or Inactive,according to one embodiment. The Default setting (which is the default)means that the profile will be public, until the neighborhood issecured; in a secured neighborhood, the profile will be Private,according to one embodiment. By changing this setting, the user mayforce the profile to be Public or Private, regardless of whether theneighborhood is secured, according to one embodiment.

For each verified residential location, the user may set edit access toGroup Editable or Self Editable, according to one embodiment.

Residential Privacy example. The residential profiles can be: Public:anyone can search, browse, or view the user profile, according to oneembodiment. This is the default setting for unsecured neighborhoods(initially, all the content on the site), according to one embodiment.Private: only people in my neighborhood can search, browse, or view theuser's profile, according to one embodiment. This is the default forsecured neighborhoods, according to one embodiment. Inactive: nobody cansearch, browse, or view the profile, even within a secured neighborhood,according to one embodiment. A user may have at least one active (publicor private), verified profile in order to have edit capabilities,according to one embodiment; if the user makes all profiles inactive,that user is treated (for edit purposes) as an unverified user,according to one embodiment.

Verified users can edit the privacy setting for their profile andoverride the default, according to one embodiment. Group Editable:anyone with access to a profile based on the privacy roles above canedit the profile, according to one embodiment. This is the defaultsetting, according to one embodiment Self Editable, only the verifiedowner of a profile can edit that profile, according to one embodiment.

Exceptions Guest User. A verified user in another neighborhood is given“Guest” access to a neighborhood for a maximum of 340 days by a verifieduser in the neighborhood in which the guest access is given, accordingto one embodiment. In effect, the guest becomes a member of theneighborhood for a limited period, according to one embodiment. Friend.When a user has self-elected being friends with someone in a differentneighborhood, they can view each other's profiles only (not theirneighbors), according to one embodiment. One way for a user to verify alocation is to submit a scanned utility bill, according to oneembodiment.

When a moderator selects the Verify Utility Bills function, the screenwill display a list of items for processing, according to oneembodiment. Accept the utility bill as a means of verification,according to one embodiment. This will verify the user's location, andwill also generate an e-mail to the user, according to one embodiment.Or Decline the utility bill as a means of verification, according to oneembodiment. There will be a drop-down list to allow the moderator toselect a reason, according to one embodiment; this reason will beincluded in an e-mail message to the user. Reasons may include: Namedoes not match, address does not match, name/address can't be read, nota valid utility bill, according to one embodiment.

In one embodiment, a method includes associating a verified registereduser (e.g., a verified registered user 4110 of FIG. 41A-B, a verifiedregistered user 4110 of FIG. 16) with a user profile, associating theuser profile (e.g., the user profile 4000 of FIG. 40A) with a specificgeographic location, generating a map (e.g., a map 1701 of FIG. 17)concurrently displaying the user profile and/or the specific geographiclocation and simultaneously generating, in the map (e.g., the map 1701of FIG. 17), claimable profiles (e.g., a claimable profile 4006 of FIG.40A-41B, a claimable profile 4102 of FIG. 41A, a claimable profile 1704of FIG. 17) associated with different geographic locations surroundingthe specific geographic location associated with the user profile (e.g.,the user profile 4000 of FIG. 40A).

In another embodiment, a system includes a plurality of neighborhoods(e.g., the neighborhood(s) 2902A-N Of FIG. 29) having registered usersand/or unregistered users of a global neighborhood environment 1800(e.g., a privacy server 2900 of FIG. 29), a social community module(e.g., a social community module 2906 of FIG. 29, a social communitymodule 2906 of FIG. 30) of the global neighborhood environment 1800(e.g., the privacy server 2900 of FIG. 29) to generate a buildingcreator (e.g., through building builder 3000 of FIG. 30) in which theregistered users may create and/or modify empty claimable profiles(e.g., the claimable profile 4006 of FIG. 40A-41B, the claimable profile4102 of FIG. 41A, the claimable profile 1704 of FIG. 17), buildinglayouts, social network pages, and/or floor levels structures housingresidents and businesses in the neighborhood (e.g., the neighborhood2900 of FIG. 29), a claimable module (e.g., a claimable module 2910 ofFIG. 29, a claimable module 2910 of FIG. 32) of the global neighborhoodenvironment 1800 (e.g., the privacy server 2900 of FIG. 29) to enablethe registered users to create a social network page of themselves,and/or to edit information associated with the unregistered usersidentifiable through a viewing of physical properties in which theunregistered users reside when the registered users have knowledge ofcharacteristics associated with the unregistered users.

In addition, the system may include search module (e.g., a search module2908 of FIG. 29, a search module 2908 of FIG. 31) of the globalneighborhood environment 1800 (e.g., the privacy server 2900 of FIG. 29)to enable a people search (e.g., information stored in people database3016 of FIG. 30), a business search (e.g., information stored inbusiness database 3020 of FIG. 30), and a category search of any data inthe social community module (a social community module 2906 of FIG. 29,a social community module 2906 of FIG. 30) and/or to enable embedding ofany content in the global neighborhood environment 1800 (e.g., theprivacy server 2900 of FIG. 29) in other search engines, blogs, socialnetworks, professional networks and/or static websites, a commercemodule (e.g., a commerce module 2912 of FIG. 29, a commerce module 2912of FIG. 33) of the global neighborhood environment 1800 (e.g., theprivacy server 2900 of FIG. 29).

The system may also provide an advertisement system to a business (e.g.,through business display advertisement module 3302 of FIG. 33) whopurchase their location in the global neighborhood environment 1800(e.g., the privacy server 2900 of FIG. 29) in which the advertisement isviewable concurrently with a map indicating a location of the business,and in which revenue is attributed to the global neighborhoodenvironment 1800 (e.g., the privacy server 2900 of FIG. 29) when theregistered users and/or the unregistered users click-in on asimultaneously displayed data of the advertisement along with the mapindicating a location of the business, a map module (a map module 2914of FIG. 29) of the global neighborhood environment 1800 (e.g., theprivacy server 2900 of FIG. 29) to include a map data associated with asatellite data which serves as a basis of rendering the map in theglobal neighborhood environment 1800 (e.g., the privacy server 2900 ofFIG. 29) and/or which includes a simplified map generator (e.g.,simplified map generator module 3402 of FIG. 34) which can transform themap to a fewer color and location complex form using a parcel data whichidentifies at least some residence, civic, and/or business locations inthe satellite data.

In yet another embodiment, a global neighborhood environment 1800 (e.g.,a privacy server 2900 of FIG. 29) includes a first instruction set toenable a social network to reside above a map data, in which the socialnetwork may be associated with specific geographical locationsidentifiable in the map data, a second instruction set integrated withthe first instruction set to enable the users (e.g., the user 2916 ofFIG. 29) of the social network to create profiles of other peoplethrough a forum which provides a free form of expression of the userssharing information about any entities and/or people residing in anygeographical location identifiable in the satellite map data, and/or toprovide a technique of each of the users (e.g., the user 2916 of FIG.29) to claim a geographic location (a geographic location 4004 of FIG.40A) to control content in their respective claimed geographic locationsand a third instruction set integrated with the first instruction setand/or the second instruction set to enable searching of people in theglobal neighborhood environment 1800 (e.g., the privacy server 2900 ofFIG. 29) by indexing each of the data shared by the users (e.g., theuser 2916 of FIG. 29) of any of the people and entities residing in anygeographic location (a geographic location 4004 of FIG. 40A).

Disclosed are a method, a device and/or a system for autonomousneighborhood multi-copter 100 commerce through a commerce server 4200 ofa neighborhood communication network, according to one embodiment.

In one aspect, an autonomous neighborhood multi-copter 100 comprising aset of wheels 301 aligned in a pattern 4610 to provide the autonomousneighborhood multi-copter 100 stability when traversing a sidewalk 112,a bike lane 307, and a roadway 114. The autonomous neighborhoodmulti-copter 100 also comprises of a storage compartment 101 of theautonomous neighborhood multi-copter 100 in which items are storable, anelectronic locking mechanism 106 of the storage compartment, a computersystem 200 of the autonomous neighborhood multi-copter 100 that iscommunicatively coupled to a commerce server 4200 of a neighborhoodcommunication system 2950 through a wireless network 2904 toautonomously navigate the autonomous neighborhood multi-copter 100 to adestination 5306 specified by the commerce server 4200, and a navigationserver 242 of the autonomous neighborhood multi-copter 100 to provide aremote sensing capability 4612 to the autonomous neighborhoodmulti-copter 100 such that the autonomous neighborhood multi-copter 100is autonomously navigable to the destination 5306.

In one embodiment, the autonomous neighborhood multi-copter 100 mayutilize a sensor fusion algorithm 238 through which at least some of anultrasound unit 228, a radar unit 222, a path lighting device 108, aLIDAR unit 224, a propeller/wheel encoding sensor 223, an accelerometersensor 219, a gyroscopic sensor 221, a compass sensor 225, and/or astereo optical sensor 227 to operate in concert to provide a threedimensional environmental view 5550 of an environment surrounding theautonomous neighborhood multi-copter 152 to the autonomous neighborhoodmulti-copter 100. The autonomous neighborhood multi-copter 100 mayinclude a sidewalk detection sensor 111 through which the autonomousneighborhood multi-copter 100 may detect a gradation rise 4600 caused bya sidewalk start location 4602 and/or a gradation drop 4604 caused by asidewalk end location 4606. A telescoping platform 107 coupled to a baseof the autonomous neighborhood multi-copter 4601 may automaticallydisplace a set of front wheels 4608 to rise and/or fall based on thedetected one of the gradation rise 4600 caused by the sidewalk startlocation 4602 and/or the gradation drop 4604 caused by the sidewalk endlocation 4606 to provide mechanical stability for contents in thestorage compartment of the autonomous neighborhood multi-copter 100.

The autonomous neighborhood multi-copter 100 may periodically transmit aheartbeat message 4260 to the commerce server 4200 having a set ofcurrent geo-spatial coordinates of the autonomous neighborhoodmulti-copter 4262, a time stamp 4264, a date stamp 4266, and/or anoperational status of the vehicle 4268. In one embodiment, theautonomous neighborhood multi-copter 100 automatically may generate anemergency broadcast message 5702 to a set of neighbors 2902 in ageo-spatial vicinity 5302 of the autonomous neighborhood multi-copter100 when the autonomous neighborhood multi-copter 100 detects a failurecondition 5703 comprising an impact 5704, a mechanical failure 5706, anelectrical failure 5708, and/or a damage condition 5718. The emergencybroadcast message 5702 may include a photo data 5714, a geo-spatialcoordinates data 5720, a video data 5710, an audio data 5712, a timeoutcondition of the heartbeat message receipt 5716 at the commerce server4200, and/or a textual data associated with the failure condition 5703.The autonomous neighborhood multi-copter 100 may automatically parkitself in a garage structure 5600 associated with an operator of theautonomous neighborhood multi-copter 100 5602 adjacent to a passengervehicle 5604, wherein the operator is at least one an individual, afamily, a business, an owner, and/or a lease, according to oneembodiment.

The storage compartment may be temperature regulated to maintain atemperature 5305 of an item 4502 in transit between a starting address5308 associated with a merchant 5310 and/or a neighbor 2920 in aneighborhood 2902 in a geospatial vicinity 5302 of the autonomousneighborhood multi-copter 100, and/or a destination 5306 addressassociated with a recipient 4214 of the item 4502 in the neighborhood2902 in the geospatial vicinity 5302 of the autonomous neighborhoodmulti-copter 100, wherein a neighborhood boundary 5303 is definedthrough a neighborhood boundary data provider 4249. In one embodiment,the autonomous neighborhood multi-copter 100 may be in a form 4302 of anautonomous neighborhood aerial vehicle 4300 having a detachable storagecompartment 4301 thereon, and/or having an ability 303 to autonomouslytraverse through bicycle lanes adjacent to a roadway 114 based oncommands from the commerce server 4200.

In another aspect, a method of an autonomous neighborhood multi-copter100 comprising associating the autonomous neighborhood multi-copter 100with a non-transient location 5418 and determining, through a commerceserver 4200 of a neighborhood communication system 2950, that adestination 5306 in a threshold radial distance 4219 from thenon-transient location 5418 is received by the autonomous neighborhoodmulti-copter 100 through a wireless network 2904. The method alsoincludes determining an optimal route 802 from the current location ofthe autonomous neighborhood multi-copter 5406 to the destination 5306and traveling autonomously on the optimal route 802 to the destination5306.

In one embodiment, the method may include periodically determining,through a processor 202, a current location of the autonomousneighborhood multi-copter 5406, communicating the current location ofthe autonomous neighborhood multi-copter 5406 to the commerce server4200, and automatically activating a set of light emitting diodes 270encompassing the autonomous neighborhood multi-copter 100 when a lightsensor 272 detects that an environmental brightness 117 is below athreshold luminosity 5307. The method may include creating an envelope900 around the autonomous neighborhood multi-copter 100, wherein theenvelope 900 includes a set of minimum ranges 902. The set of minimumranges 902 may include a minimum distance that must be kept in adirection in front 916, a direction behind 918, a direction to a left913, a direction to a right 914, above, and/or below the autonomousneighborhood multi-copter 100.

The method may include establishing a range of speed 5721 the autonomousvehicle may reach and establishing a distance traveled 5420 range by theautonomous neighborhood multi-copter 100, wherein the distance traveled5420 range by the autonomous neighborhood multi-copter 100 is set for aper trip, per day and/or a per delivery distance traveled 5420. In oneembodiment, the method may include establishing a maximum magnitude ofdeceleration 5372, wherein the maximum magnitude of deceleration 5372 ismeasured in feet per second squared, and establishing a minimumcrosswalk proximity 5204 at which the autonomous neighborhoodmulti-copter 100 is permitted to stop.

The method may include determining at a predetermined interval 5374 if adifferent route 804 that is more efficient than the optimal route 802exists based on a delivery time 5424, a pendency of time, and/or aminimal travel distance 5426. The predetermined interval 5374 fordetermining if a different route 804 is more efficient than the optimalroute 802 exists may include constantly determining, determining everyminute, determining different route 804 every one hundred yard, when theautonomous neighborhood multi-copter 100 encounters traffic, when theautonomous neighborhood multi-copter 100 encounters the object 408. Themethod may include calculating the different route 804 and travelingalong the different route 804 as long as the different route 804 remainsa most efficient route. In one embodiment, the method may includedetermining when an alternate field of view 502 is needed, prioritizingestablished constraints of the envelope 900, the speed 5307, thedistance traveled 5420, the maximum magnitude of deceleration 5372and/or the minimum crosswalk proximity 5204 in respect to the need toestablish the alternate field of view 502, determining an optimalalternate field of view 504 that does not violate establishedconstraints prioritized above obtaining the alternate field of view 502,and obtaining the optimal alternate field of view 504 without violatingconstraints prioritized above obtaining the alternate field of view 502.

In one embodiment, obtaining the optimal alternate field of view 504without violating constraints prioritized above obtaining the alternatefield of view 502 involves switching sensors, moving the autonomousneighborhood multi-copter 100 and/or moving sensors. The set of minimumranges 902 of the envelope 900 may depend on a speed 5307 of theautonomous neighborhood multi-copter 100, a set of weather conditions119, an environment of the autonomous neighborhood multi-copter 152, theitem 4402, and/or a nature of the object 409 that is in close proximitywith the autonomous neighborhood multi-copter 100. The storagecompartment may be temperature regulated to maintain a temperature 5305and/or a humidity 5376 of an item 4502 in transit between a startingaddress 5308 associated with a merchant 5310 and/or a neighbor 2920 in aneighborhood 2902 in a geospatial vicinity 5302 of the autonomousneighborhood multi-copter 100, and/or a destination 5306 locationassociated with a recipient 4214 of the item 4502 in the neighborhood2902 in the geospatial vicinity 5302 of the autonomous neighborhoodmulti-copter 100. In one embodiment, the neighborhood boundary 5303 maybe defined through a neighborhood boundary data provider 4249, and/orthe storage compartment 101 may be equipped with a suspension device4506 to protect the item 4502 while in transit.

The method may include automatically generating an emergency broadcastmessage 5702 to a set of neighbors 2902 in a geo-spatial vicinity 5302of the autonomous neighborhood multi-copter 100 when the autonomousneighborhood multi-copter 100 detects a failure condition 5703comprising an impact 5704, a mechanical failure 5706, an electricalfailure 5708, and/or a damage condition 5718, wherein the emergencybroadcast message 5702 includes a photo data 5714, a geo-spatialcoordinates data 5720, a video data 5710, an audio data 5712, a timeoutcondition of a heartbeat message 4260 receipt 5716 at the commerceserver 4200, and/or a textual data associated with the failure condition5703. In one embodiment, the method may include periodicallytransmitting a heartbeat message 4260 to the commerce server 4200 havinga set of current geo-spatial coordinates 4262 of the autonomousneighborhood multi-copter 100, a time stamp 4264, a date stamp 4266,and/or an operational status 4268 of the vehicle. The method may includeautomatically contacting emergency response services when the autonomousneighborhood multi-copter 100 detects a crime 5707, an accident 5705involving third parties and/or an attempted tampering 5709 with theautonomous neighborhood multi-copter 100.

The contacting may include a time stamp 4264, the geo-spatialcoordinates data 5720, the photo data 5714, the video data 5710, theaudio data 5712, and/or the textual data, and/or wherein emergencyresponse services include a police station 5713, a fire station 5711and/or a medical responder 5715. In one embodiment, the method mayinclude calculating a set of predicted behaviors 305 of detected objectswithin a threshold distance 4214 from the autonomous neighborhoodmulti-copter 100 and determining confidence levels 307 for the predictedbehaviors 305, wherein the confidence levels 307 are a number and/or apercentage 313 of the probability of each predicted behavior occurring.The method may include adjusting confidence levels 307 for the predictedbehaviors 305 based on a change in location 311, a change in speed 306,a change of direction 309, a change in angle 308 and/or observedbehavior, according to one embodiment. The method may include vending anitem 4502 from the storage compartment and ejecting the item 4502 froman ejection module 110, wherein the item 45012 is ejected through an airbased propulsion system 4406 aligned through a camera adjacent to theejection module 4408.

In one embodiment, the method may include detecting a stop sign 5206and/or automatically stopping the autonomous neighborhood multi-copter100 at the appropriate point when the stop sign 5206 is detected,detecting a yield sign 5208 and/or automatically monitoring and/oryielding to a traffic flow 5210 at an intersection 5200 in theneighborhood 2902, detecting when a pedestrian 904 is walking in a path903 proximate to the autonomous neighborhood multi-copter 100, and/ordetecting when a bicyclist 302 is biking in a path 903 proximate to theautonomous neighborhood multi-copter 100. The method may includeaccepting a credit payment 5420 using a magnetic card reader 4508 of theautonomous neighborhood multi-copter 100, a near-field credit scanner ofthe autonomous neighborhood multi-copter 100, and/or a biometric paymentreader 4410 of the autonomous neighborhood multi-copter 100. Thecommerce server 4200 may be in a privacy server 2900 of the neighborhoodcommunication system 2950 that may be wirelessly coupled with theautonomous neighborhood multi-copter 100.

The privacy server 2900 may be a community network 4250 comprisingverifying that each user of the community network 4250 lives at aresidence 2918 associated with a claimable residential address 115 ofthe community network 4250 formed through a social community module 2906of a privacy server 2900 using a processor 202 and/or a memory. Theprivacy server 2900 may be a community network 4250 comprising obtainingfrom each user of the community network 4250, using the processor 202 ofa data processing system 4204, member data 5738 associated with eachuser, the member data 5738 including an address 5740, and associatingthe address with a profile 5742 of each user. In one embodiment, theprivacy server 2900 may be a community network 4250 comprisingdetermining a location of each user based on the member data 5738,storing the member data 5738 in a database 4222, and obtaining apersonal address privacy preference 5744 from each user, the personaladdress privacy preference 5744 specifying if the address should bedisplayed to other users.

The method may include generating, using a mapping server 2926associated with the privacy server 2900 through a network 2904, ageospatial representation of a set of points 5732 on a map 5734 definingresidences 2918 associated with each user of the community network 4250having the member data 5738, and authenticating, using a verify module3006 of the privacy server 2900, a particular user 5422 of a third-partyapplication as being a verified user 4110 of the neighborhoodcommunication system 2950 having a verified residential address 5378 inthe neighborhood communication system 2950. In one embodiment, themethod may include communicating, using the verify module 3006 of theprivacy server 2900, a social graph of the particular user 5422 based onthe personal address privacy preference 5744 of the particular user 5422to the third-party application. The method may include providing, usingthe verify module 3006 of the privacy server 2900, the verifiedresidential address 5378 to the third-party application based on theauthentication of the particular user 5422 of the third-partyapplication as being the verified user 4110 of the neighborhoodcommunication system 2950.

The privacy server 2900 communicatively coupled with the mapping server2926 through the network 2904 may apply an address verificationalgorithm 2903 associated with each user of the online community 5730 toverify that each user lives at a residence 2918 associated with aclaimable residential address 115 of an online community 5730 formedthrough a social community module 2906 of the privacy server 2900 usingthe processor 4220 and/or the 4224 memory. The mapping server 2926 maygenerate a latitudinal data 5724 and/or a longitudinal data 5722associated with each claimable residential address 115 of the onlinecommunity 5730 associated with each user of the online community 5730.The privacy server 2900 may automatically determine a set of accessprivileges in the online community 5730 associated with each user of theonline community 5730 by constraining access in the online community5730 based on a neighborhood boundary 5303 determined using a Beziercurve algorithm 3040 of the privacy server 2900. The privacy server 2900may transform the claimable residential address 115 into a claimedaddress 4247 upon an occurrence 5728 of an event 5726.

The privacy server 2900 may instantiate the event when a particular user5422 is associated with the claimable residential address 115 based on averification 5746 of the particular user 5422 as living at a particularresidential address 5748 associated with the claimable residentialaddress 115 using the privacy server 2900. The privacy server 2900 mayconstrain the particular user 5422 to communicate through the onlinecommunity 5730 only with a set of neighbors 2920 having verifiedresidential addresses 5378 using the privacy server 2900. The privacyserver 2900 may define the set of neighbors 2920 as other users of theonline community 5730 that have each verified their addresses in theonline community 5730 using the privacy server 2900 and/or which haveeach claimed residential addresses that are in a threshold radialdistance 4219 from the claimed address of the particular user 5422.

In yet another aspect, a neighborhood communication system 2950comprising a commerce server 4200, a wireless network 2904, and a set ofautonomous neighborhood multi-copters 100 that are communicativelycoupled to the commerce server 4200 of the neighborhood communicationsystem 2950 through the wireless network 2904 to autonomously travel todestinations 5306 specified by the commerce server 4200. Each of the setof autonomous neighborhood multi-copters 100 periodically transmitsheartbeat messages 5700 to the commerce server 4200 having a set ofcurrent geo-spatial coordinates 4262 of each of the autonomousneighborhood multi-copters 100, a time stamp 4264, a date stamp 4266,and an operational status 4268 of each of the autonomous neighborhoodmulti-copters 100. At least some of the autonomous neighborhoodmulti-copters 100 are in a form 4302 of autonomous neighborhood bicycles4300 each having a detachable storage compartment 4301 thereon, andhaving an ability 303 to autonomously traverse through bicycle lanesadjacent to a roadway 114 based on commands from the commerce server4200.

In one embodiment, each of the autonomous neighborhood multi-copter 100utilizes a sensor fusion algorithm 238 through which at least some of anultrasound unit 228, a radar unit 222, a light sensor 272, a LIDAR unit224, a propeller/wheel encoding sensor 223, an accelerometer sensor 219,a gyroscopic sensor 221, a compass sensor 225, and/or a stereo opticalsensor 227 to operate in concert to provide a three dimensionalenvironmental view 5550 to the autonomous neighborhood multi-copter 100of an environment surrounding each of the autonomous neighborhoodmulti-copter 152. A particular autonomous neighborhood multi-copters 100may automatically generate an emergency broadcast message 5702 to a setof neighbors 2920 in a geo-spatial vicinity of the particular autonomousneighborhood multi-copter 5302 when the particular autonomousneighborhood multi-copter 100 detects a failure condition 5703comprising an impact 5704, a mechanical failure 5706, an electricalfailure 5708, and/or a damage condition 5718, wherein the emergencybroadcast message 5702 includes a photo data 5714, a geo-spatialcoordinates data 5720, a video data 5710, an audio data 5712, a timeoutcondition of the heartbeat message 4260 receipt 5716 at the commerceserver 4200, and/or a textual data associated with the failure condition5703.

Each of the autonomous neighborhood multi-copters 100 automatically maybe able to park themselves in a garage structure 5600 associated with anoperator of the autonomous neighborhood multi-copter 5602 adjacent to apassenger vehicle 5604, wherein the operator 5602 is at least one anindividual, a family, a business, an owner, and/or a lease. The storagecompartment may be temperature regulated to maintain a temperature 5305of an item 4502 in transit between a starting address 5308 associatedwith a merchant 5310 and/or a neighbor 2920 in a neighborhood 2902 in ageospatial vicinity 5302 of the autonomous neighborhood multi-copter100, and/or a destination 5306 address associated with a recipient 4214of the item 4502 in the neighborhood 2902 in the geospatial vicinity5306 of the autonomous neighborhood multi-copter 100, wherein theneighborhood boundary 5303 is defined through a neighborhood boundarydata provider 4249.

An example embodiment will now be described. In an example embodiment,Jenny may wish to sell some items in her home. She may alert herneighbors and/or inform them about the items for sale via the garagesale server 100. Many of her neighbors may attend her garage sale.However, some neighbors who may be interested in certain items may beunable to travel to Jenny's house. These neighbors may be busy duringthe time of the garage sale and/or may not have access totransportation. Jenny may still be able to deliver items to theseneighbors by using the autonomous neighborhood multi-copter 100 (e.g.,the autonomous delivery box multi-copter).

Jenny's neighbor, Joe, may want to purchase her old computer that waslisted through the garage sale server 100 as being included in thegarage sale. Joe may be unable to attend the garage sale in person.Jenny may be able to place the computer in and/or on the autonomousneighborhood multi-copter 100 and enter a destination directly throughthe autonomous neighborhood multi-copter 100 and/or using the dataprocessing system 104. The autonomous neighborhood multi-copter 100 maybe able to autonomously deliver the computer to Joe's location using themultidirectional camera(s) 1202 and/or the GPS device while keeping theitem safe in transit (e.g., using the lock 1204). The autonomousneighborhood multi-copter 100 may be able to travel on sidewalks, theside of the road, in bike paths etc. and/or navigate traffic, redirectto an optimal route, and/or obey traffic laws while making the delivery.Once the autonomous neighborhood multi-copter 100 reaches thedestination, a text may be sent to Joe containing the passcode to thelock 1204. Joe may be able to open the lock 1204 and retrieve his newcomputer without leaving his home.

In another example embodiment, Jenny may have broken her leg and beunable to get out of bed. Her family may be out of town and she may havenobody to help her get groceries. Jenny may be able to use theautonomous neighborhood multi-copter 100 (e.g., use her own, rent onefrom a neighbor, a company and/or the geospatially constrained socialnetwork 4242) to receive food from a local grocery store. Jenny may beable to use the geospatially constrained social network 4242 to send theautonomous neighborhood multi-copter 100 to the store. She may be ableto send the store (e.g., employee working at the store, the store'sprofile on the geospatially constrained network etc.) a shopping listand/or may instruct the autonomous neighborhood multi-copter 100 torelay the list to the store.

An employee at the store may load the requested items into theautonomous neighborhood multi-copter 100 and the vehicle may travelautonomously in the manor detailed above to Jenny's location, deliveringthe groceries. In one embodiment, a financial transaction may be carriedout through the garage sale server 100. Similar pick-ups and/ordeliveries may be conducted with other entities such as Target©,Amazon©, retail stores, etc.

In another embodiment, a neighbor ‘Sam’ may wish to sell his old iPhoneto a neighbor Phil. Sam may use the Fatdoor app on his mobile phone tosell his iPhone to neighbor Phil. Sam may summon the Fatdoor rover(e.g., an autonomous neighborhood multi-copter 100 in Sam'sneighborhood) to come and pick up his old iPhone. The Fatdoor rover maybe dispatched from a central location near City Hall, and come and pickup Sam's iPhone. When the Fatdoor rover is arriving in a few minutes,Sam's phone may get a text alert, notifying that Sam should load therover once it arrives near his home in a few minutes. The text messagemay include an ‘unlock’ code to a storage chest (e.g., the storagecompartment 101) of the autonomous Fatdoor rover. Sam may us the unlockcode (e.g., using a near-field communication technology such as iBeacon,NFC and/or a keypad unlock code) to unlock the storage chest of theautonomous Fatdoor Rover (e.g., the autonomous neighborhood multi-copter100). Once loaded, Sam may secure the cavity of the Fatdoor rover, andthe rover may travel to a location of Phil's home to deliver the iPhone.Once near Phil's home, Phil may also receive a text message notifyingthat the autonomous rover is near his front porch and a unique unlockcode (e.g., which may expire after a period of time). Once Phil receivesthe iPhone, Sam may get paid by Phil. Until then, money may be held inan escrow account with Fatdoor, Inc. In an alternate embodiment, Sam mayget paid earlier as soon as he enters into a contract with Phil. TheFatdoor rover may know how to get to Sam's house and/or Phil's housebased on a ‘pick up’ address of Sam and a ‘delivery’ address of Philentered during the transaction. Further, an optimal pickup time mayguide the Fatdoor rover to pick up and deliver items at desired times inthe neighborhood. The Fatdoor rover may be an electric vehicle with alimited 25 to 40 mile round trip range. Further, the Fatdoor rover maytravel on sidewalks and/or bicycle lanes at a maximum speed of 30 milesper hour. The Fatdoor rover may have upon it a camera (e.g., a LIBORcamera), infrared sensors, laser sensors, and on board navigation.

In another embodiment, Phil may purchase a pizza from the neighborhood‘Famiglia Pizzaria’, the best pizza this side of Texas through hisdesktop computer using Fatdoor (e.g., and/or another website such asfamiliapizzariaofHouston.com having the Fatdoor Connect APIintegration). Famiglia Pizzaria may have purchased two Fatdoor roversfor pizza deliveries in the neighborhood. Once Phil places an order forpizza, the Fatdoor rovers (branded on the side with Famiglia Pizzaria)may deliver pizza's to Phil's house once the pizzas come out of theoven. Phil may be able to track and view the progress and estimateddelivery time of his pizzas through his mobile device, and may even seethe current location of the Fatdoor rover assigned to deliver his pizzato him. The storage compartment of the Fatdoor rovers used by Famigliapizza may be heated to keep the pizzas warmth while in route. TheFatdoor rovers (e.g., the autonomous neighborhood multi-copter 100) maykeep a log and centrally store the video that they capture to ensurethat there is no theft and/or breach of security of the storagecompartment during transit. Further, the Fatdoor rovers may be able tosafely be able to navigate over sidewalks, yield signs, stop signs,people, bikes, and cars in the roads as they navigate from FamigliaPizzaria to Phil's home. Once the pizzas are delivered, the Fatdoorrovers purchased by Famiglia may automatically make their way back toFamiglia's pizza headquarters for the next delivery.

An example embodiment will now be described. A person confronted with anemergency situation (e.g. the user 2916, the verified user 3506) maysend a broadcast on a geospatially constrained social network 4200 (e.g.Fatdoor.com, Nextdoor.com). To accomplish this broadcast the person maygenerate the broadcast data 2902 which will be sent to the privacyserver 2900 to generate the notification data 4212. The notificationdata 4212 may include any information contained in the broadcast data2902 such as the geospatial location, time, date, a textual descriptionand live broadcast of audio and/or video generated by the user 2916. Thenotification data 4212 may then be radially distributed in the area witha threshold radial distance 4219 of the epicenter 4244 that may be thelocation of the device observing the emergency. The person may be hopingfor immediate assistance from other people living nearby (e.g. therecipients (e.g., other users of the neighborhood communication system2950 such as neighbors 2920 of FIG. 29)) to help confront the emergencysituation. Rather than attempt to contact those living nearbyindividually, the person experiencing the emergency may broadcast thenotification 4212 to proximate neighbors simultaneously, maximizing thechance that a relevant person will appreciate, view and/or respond tothe broadcast.

Additionally, for example, the broadcast may even occur automaticallyupon the dialing of neighborhood services as to allow concurrentnotification of nearby recipients (e.g., other users of the neighborhoodcommunication system 2950 such as neighbors 2920 of FIG. 29) withoutdetracting from a conventional mode of contacting emergency services(e.g. the emergency call 4000). The emergency call 4000 may be monitoredby the privacy server 2900 to automatically generate the neighborhoodbroadcast data, including live audio of the call which the privacyserver 2900 may use to create a transcript 4004. The transcript 4004,along with metadata from the call that may include the geospatiallocation of the mobile device on which the call was made may then bebroadcast according to the social community module 2906 to nearbyrecipients (e.g., other users of the neighborhood communication system2950 such as neighbors 2920 of FIG. 29). The recipients (e.g., otherusers of the neighborhood communication system 2950 such as neighbors2920 of FIG. 29) may then be notified of the emergency situation and/orprompted to respond without detracting from a call to the neighborhoodservices.

For example, in an elementary school setting (e.g., the threshold radialdistance 4219 may be set to a boundaries of the elementary school usingthe Bezier curve algorithm 3040 of the social community module 2906). Aprincipal of the Sacred Brooks Elementary School Mr. Higgins may heargunshots that he believes are coming from an on-campus location. Screamsof panicked teachers and children may soon follow. Mr. Higgins may usehis mobile device (e.g., his cellular phone) to call an emergency number‘911’. Calling this emergency number ‘911’ may also trigger an automaticalert to the privacy server 2900 to generate the neighborhood broadcastdata (or alternatively Mr. Higgins may separately send an emergencybroadcast (e.g., a neighborhood broadcast using the Bezier curvealgorithm 3040 of the social community module 2906) using the Fatdoormobile application). All teachers at the school and parents in adjacentneighborhoods may be instantly notified (e.g., through the creation ofthe neighborhood broadcast data distributed as the notification data4212).

Wilson Brighton at the Fatdoor Emergency Center may receive a messagethat there is an emergency at the Sacred Brooks Elementary school.Wilson Brighton may open up a communication channel with Mr. Brightonand invite adjacent neighborhoods and medical professionals havingclaimed profiles and/or living in the area to help. In addition, Wilsonmay merge the emergency transmissions into a single session so that Mr.Higgins initial emergency broadcast (e.g., a neighborhood broadcastusing the Bezier curve algorithm 3040 of the social community module2906) is automatically merged with related other broadcasts by teachers,parents, staff, and children at the school. This single thread ofbroadcasts related to the Sacred Brooks Elementary school may beprovided as live-feed emergency broadcast (e.g., a neighborhoodbroadcast using the Bezier curve algorithm 3040 of the social communitymodule 2906)s to all users of Fatdoor.com having a claimed profile(e.g., a home address and/or a work address) within the threshold radialdistance 4219 from Mr. Higgins (e.g., the epicenter 4244 of thebroadcast). Even when parents are at work, they may still receive thebroadcast live on their mobile devices because they have downloaded theFatdoor application and have claimed their home/business address arounda location of the emergency.

As a result, local neighborhood parents may arrive from their worklocations, even when they work at a different location than where theylive. This may save lives at the Sacred Brooks elementary school becausehelp may arrive sooner.

For example, one recipient of Mr. Higgin's broadcast may be SamuelWilson (“Sam”), who has two children at Sacred Brooks Elementary School:John, a bright kindergartener 6, and Samantha, a talented artist of age10. Sam may be alerted even when he is at work on a construction site 6miles away from the Sacred Brooks Elementary School where John andSamatha are located. Sam may receive an alert on his mobile phone thatthere is an emergency in his neighborhood. Jumping into his truck, Sammay drive to the school to render assistance, tuning in to the livebroadcast as events unfold. Others may join in and as well andcommunicate and provide instructions and reassurance to Mr. Higgins andother broadcasters.

Nearby resident Chen Su, whose backyard fence adjoins the playground ofSacred Brooks, may also receive the broadcast. Chen may run outside andunlock his gate, opening it so that children may not be trapped in theplayground area. Chen may then send a separate broadcast a new escaperoute has been established. Mr. Higgins may gather as many nearbychildren as he can and lead them safety through Chen's gate.

Henry Stewart, a decorated army veteran who lives a few blocks away fromSacred Brooks Elementary, may also receive the broadcast. Alarmed forthe safety of the children, and knowing that it may take the policeseveral minutes to arrive at the school, Henry may decide that it willmaximize the children chance at survival if he is the first responder.Equipping his .22 caliber rifle, he may run to the school and distractor defeat the shooter in time to save many lives.

Similarly, Dr. Juan Sanchez, M.D. may have an office in the neighborhoodimmediately adjacent to Sacred Brooks. Dr. Sanchez and his team ofmedical professionals may rush to the scene, engaging in bi-directionalcommunications with the school staff during the live broadcast event sothat he knows exactly which building to arrive at. Calming victims andputting pressure on wounds until ambulances arrive, Dr. Sanchez and histeam may save the lives of wounded children.

When the incident is over, many people may want to recreate the eventsfor journalistic or evidentiary purposes. They may also want to studygenerally the flow of information during emergencies in theirneighborhood, and decide how their school could better prepare.Similarly, they may want to ensure they are part of the broadcast systemin cast there are future incidents. Persons who have not yet claimedtheir verified profiles in the area surrounding Sacred Brooks ElementarySchool on Fatdoor may go online and find profiles pre-seeded with dataassociated with their address. Those pre-seeded profiles may have beenupdated with local broadcasts. These people may be able to claim theirprofile and have access to previous broadcasts, including thoseassociated with the school shootings. This may help them to betterprepare for the safety of their children.

Because of the technologies described herein, the neighborhood, city,and country is a better place because emergency response teams aresupplemented with information from those who have a claimed geo-spatiallocation around a neighborhood in which there is trouble. In addition,evidence may be formed that is admissible to prove guilt of the gunmen,defeat a defense of insanity, or impose a maximum sentence.

In another example, a user Bob Jones may be walking around Menlo Park,Calif. when he observes a robber pull out a knife and threaten to harmPaula Nelson in a parking lot if she does not give the robber her carkeys. Bob may take out his mobile device and select the emergencylisting criteria “major violent crime” in the user interface of themobile application that communicates with the emergency response server.Bob may center his viewfinder on the unfolding robbery and select the“broadcast live” indicator on the user interface, as well as enteringthe brief description “Car jacking in progress” in a small data field.The broadcast data, including live video and audio, may be generated andsent to the emergency response server where it may be radiallydistributed to user profiles at a threshold radial distance 4219 fromthe epicenter 4244 centered on Bob's mobile device. Because Bobspecified the emergency as a “major violent crime” its threshold radialdistance 4219 may be larger than if Bob had selected mere “vandalism.”

To further illustrate, several relevant parties may receive thebroadcast. Patrick Sloan, an off-duty police detective, is alerted toBob Jones' broadcast data by a notification sent to his mobile device.Patrick, looks his mobile device to read Bob's brief description, andnotices that the event is only “0.3 miles away.” Patrick selects the“respond indicator” to let Bob know he is on his way, and also selects“dial broadcaster” to establish a bi-directional communication with Bob.A map on Patrick's mobile device and a set of directions may showPatrick the fastest way to travel to the epicenter 4244, along withwarning Patrick when he is within 2900 yards of the emergency.

Jason Steinbrenner, a retired surgeon, also receives Bob's broadcast.Jason opts to view Bob's live video feed. Jason notices that the robberseverely lacerates Paula with his knife as he grabs Paula's keys away.Jason sees that he is only 0.7 miles away from the emergency and alsoselects the “respond indicator” to let Bob know he will arrive shortly.Through his user interface he sends Bob a text message “I'm a doctor.”

Jane Doe, a resident living within the threshold radial distance 4219also receives Bob's broadcast. Jane, while viewing Bob's live feed,takes note of the vehicle make, model and color. As the robber gets inPaula's car and drives away, out of Bob's view, Jane goes to herapartment window and looks outside. A minute later, Jane sees thewoman's car, driven by the robber, headed down her street, trying tokeep a low profile. Jane generates her own broadcast including a videofeed of the car stopped at a stoplight. Patrick Sloan, driving his carto reach Bob's location, receives Jane's broadcast. Patrick, now usingJane's epicenter 4244, redirects his path to intercept the robber. UsingJane's live video broadcast to remotely view the intersection, Patrickis able to safely approach the robber from behind and surprise him atthe stoplight, capturing him.

Emergency services, which may subscribe to all emergency broadcast(e.g., a neighborhood broadcast using the Bezier curve algorithm 3040 ofthe social community module 2906)s within the threshold radial distance4219 of the epicenter 4244, may also have been notified. The policedepartment and an ambulance arrive after Patrick catches the robber andJason stabilizes the woman.

Bob and Jane may receive a summary of their broadcast data that showsthem how many recipients received his broadcast, the emergency servicescontacted, and who was responding. Their broadcast submissions may alsoinclude a unique identifies such that the live video, recorded by theemergency response server, which may be later retrieved to provideevidence against the robber with a unique identification code.

Because of the emergency response sever described in FIGS. 1-11, Jasonwas able to arrive on the scene faster than emergency services, puttingpressure on Paula's wound to prevent detrimental bleeding. The broadcastsystem also allowed Patrick to catch the perpetrator both because he wasa concerned local resident and because other nearby residents, such asJane, were alerted by Bob's original broadcast and were thereforeprepared to provide additional helpful broadcasts.

Bob and Jane may live in the Lorelei neighborhood of Menlo Park, and forthis reason receive the emergency broadcast data (e.g., a neighborhoodbroadcast generated by the social community module 2906). If Bob createsan emergency broadcast, Bob may choose to restrict dissemination of hisemergency broadcast just to the Lorelei neighborhood because it is an‘active’ neighborhood around where Bob lives. Particularly, a minimumnumber of Bob's neighbors in the Lorelei neighborhood, such as 10neighbors in the Lorelei neighborhood, may have signed up and verifiedtheir profiles through an online neighborhood social network (e.g.,Fatdoor.com). If Bob is the first user that creates a private networkfor his neighborhood (e.g., a ‘founding member’), he may need to drawgeospatial boundaries and/or claim geospatial boundaries around hisneighborhood and invite a threshold number of neighbors (e.g., 10neighbors) to activate it. An amount of time for Bob to invite andactivate his neighborhood may be limited (e.g., 21 days). However, Bobmay request an extension of time from the privacy server 2900 if Bobneeds more time to invite users, and the privacy server 2900 may grantthis extra time. In other words, if Bob is a founding member, he mayhave the ability to define the neighborhood boundary and choose theneighborhood name.

The privacy server 2900 may internally make corrections to either theboundaries or name that Bob set based on feedback from other neighborsand/or based on internal policies. These internal policies may include apreference for a use of official names for a community (e.g., based onlocal thoroughfares, a nearby park, or landmark for inspiration), aneighborhood name that is short and sweet (e.g., eliminating unnecessarywords like city, state, neighbors, neighborhood, HOA, friends, etc.),with correct capitalization (e.g., to ensure that a first letter of eachword is capitalized), and/or use of spaces between each word in aneighborhood name. In one embodiment, Bob may designate neighborhood‘leads’ who can adjust boundaries of their neighborhood through anadjust boundaries tool. Bob may be part of an elite group ofneighborhood ‘leads’ who keep the privacy server 2900 operating smoothlyby organizing information and posting neighborhood-wide information. Theneighborhood leads like Bob may have special privileges such as removinginappropriate messages, adjusting neighborhood boundaries, verifyingunverified members, editing the about section on a neighborhood feed,and/or promoting other members to become neighborhood leads.

Bob and his neighbors may have each verified their addresses through apostcard verification system in which they received a postcard at theirhome with an access code that permits each of them to access theirprivate Lorelei neighborhood community information including emergencybroadcast alerts in the online neighborhood social network (e.g., theFatmail postcard system through which an access code may have beenreceived at a respective Lorelei home that uniquely identifies andverifies a home in the Lorelei neighborhood). Bob may have invited athreshold number (e.g., 10) of his Lorelei neighbors prior to theLorelei neighborhood becoming active. Bob may choose to disseminate hisemergency broadcast data to a neighborhood adjacent to Lorelei, such asMenlo Park downtown (e.g., using the Bezier curve algorithm 3040 of thesocial community module 2906). Optionally, Bob may choose to restricthis emergency broadcast data just to Lorelei neighbors (e.g., using theBezier curve algorithm 3040 of the social community module 2906). Inother words, users of the neighborhood social network in an entirelydifferent neighborhood, such as the Financial District neighborhood ofSan Francisco (about 20 miles away) may not be able to access theemergency broadcast data that Bob generates.

For example, the emergency broadcast data may be disseminated toadjacent neighborhoods that have been claimed by different users in amanner such that the emergency broadcast data is optionally disseminatedto the surrounding claimed neighborhoods based on Bob's preference.

It will be understood with those skill in the art that in someembodiments, the social community module 2906 may restrict disseminationof broadcast data by verified users to claimed neighborhoods in aprivate neighborhood social network (e.g. the privacy server 2900 may bea private social network, the neighborhood curation system describedherein may also be part of the private neighborhood social network) inwhich the broadcaster resides (e.g., has a home) using the radialalgorithm 4241 (e.g., the Bezier curve algorithm 3040 of FIG. 30). Theprivacy server 2900 may include online communities designed to easilycreate private websites to facilitate communication among neighbors andbuild stronger neighborhoods (e.g., to help neighbors build stronger andsafer neighborhoods).

Further, it follows that the threshold radial distance 4219 generatedthrough the Bezier curve algorithm 3040 of FIG. 30 may take on a varietyof shapes other than purely circular and is defined to encompass avariety of shapes based on associated geographic, historical, politicaland/or cultural connotations of associated boundaries of neighborhoodsand/or as defined by a city, municipality, government, and/or dataprovider (e.g., Maponics®, Urban Mapping®), in one embodiment. Forexample, the threshold radial distance 4219 may be based on a particularcontext, such as a school boundary, a neighborhood boundary, a collegecampus boundary, a subdivision boundary, a parcel boundary, and/or a zipcode boundary. In an alternate embodiment, a first claiming user 2916 ina particular neighborhood may draw a polygon to indicate a preferredboundary.

In an alternative embodiment, the threshold radial distance 4219generated using the Bezier curve algorithm 3040 by the privacy server2900 may be restricted to a shared apartment building (e.g., and/or anoffice building). In addition, it will be understood with those skilledin the art that the privacy server 2900 may be operate as a function ofthe privacy server 2900 (e.g., a neighborhood social network).

In addition, it will be understood that in some embodiments, theneighborhood broadcast data is generated by the police department (e.g.,and/or others of the neighborhood services) in the form of crime alerts,health alerts, fire alerts, and other emergency alerts and provided as afeed (e.g., a Real Simple Syndication (RSS) feed) to the privacy server2900 for distribution to relevant ones of the claimed neighborhoods inthe privacy server 2900. It will be understood that the neighborhoodbroadcast data may appear in a ‘feed’ provided to users of the privacyserver 2900 (e.g., a private social network for neighbors) on theirprofile pages based on access control privileges set by the socialcommunity module module using the Bezier curve algorithm 3040. Forexample, access to the neighborhood broadcast data may be limited tojust a claimed neighborhood (e.g., as defined by neighborhoodboundaries) and/or optionally adjacent neighborhoods.

In one embodiment, the privacy server 2900 may provide policedepartments and other municipal agencies with a separate login in whichthey can invite neighbors themselves, provide for a virtual neighborhoodwatch and emergency preparedness groups, and conduct high value crimeand safety related discussions from local police and fire officialswithout requiring any technical integration. This may provide policedepartments and municipalities with a single channel to easily broadcastinformation across neighborhoods that they manage, and receive and trackneighborhood level membership and activity to identify leaders of aneighborhood.

For example, communications defined from one broadcasting user to anadjacent neighborhood o may involve sharing information about asuspicious activity that might affect several neighborhoods, explainingabout a lost pet that might have wandered into an adjoiningneighborhood, to rally support from neighbors from multipleneighborhoods to address civic issues, to spread the word about eventslike local theater production or neighborhood garage sales, and/or toask for advice or recommendations from the widest range of people in acommunity). In one embodiment, the privacy server 2900 may preventself-promotional messages that are inappropriate (e.g., a user sendingsuch messages may be suspended from the geospatially constrained socialnetwork 4242 using the crowd sourced moderation algorithm 3004. In oneembodiment, the user 2916 may personalize nearby neighborhoods so thatthe user can choose exactly which nearby neighborhoods (if any) theywish to communicate with. The user 2916 may be able to flag aneighborhood feeds from adjacent neighborhoods. In addition, leadersfrom a particular neighborhood may be able to communicate privately withleaders of an adjoining neighborhood to plan and organize on behalf ofan entire constituency. Similarly, users 2906 may be able to filterfeeds to only display messages from the neighborhood that they residein. The user 2916 may be able to restrict posts (e.g., pushpinplacements) only in the neighborhood they are presently in. In oneembodiment, nearby neighbors may (or may not) be able to access profilesof adjacent neighborhoods.

It will also be understood that in some embodiments, that users may be‘verified through alternate means, for example through a utility billverification (e.g., to verify that a user's address on a utility billmatches the residential address they seek to claim), a credit cardverification (e.g., or debit card verification), a phone numberverification (e.g., reverse phone number lookup), a privately-publishedaccess code (e.g., distributed to a neighborhood association president,and/or distributed at a neighborhood gathering), and a neighbor vouchingmethod (e.g., in which an existing verified neighbor ‘vouches’ for a newneighbor as being someone that they personally know to be living in aneighborhood.

In one embodiment, the privacy server 2900 ensures a secure and trustedenvironment for a neighborhood website by requiring all members toverify their address. In this embodiment, verification may provideassurance the assurance that new members are indeed residing at theaddress they provided when registering for an account in the privacyserver 2900. Once a neighborhood has launched out of pilot status, onlymembers who have verified their address may be able access to theirneighborhood website content.

It will be understood that among the various ways of verifying anaddress, a user of the privacy server 2900 may uses the followingmethods to verify the address of every member:

A. Postcard. The privacy server 2900 can send a postcard to the addresslisted on an account of the user 2916 with a unique code printed on it(e.g., using the Fatmail postcard campaign). The code may allow the user2916 to log in and verify their account.

B. Credit or debit card. The privacy server 2900 may be able to verify ahome address through a credit or debit card billing address. In oneembodiment, billing address may be confirmed without storing personallyidentifiable information and/or charging a credit card.

C. Home phone. If a user 2916 has a landline phone, the user may receivean automated phone call from the privacy server 2900 that may providewith a unique code to verify an account of the user 2916.

D. Neighborhood leader. A neighborhood leader of the geospatiallyconstrained social network can use a verify neighbors feature of theprivacy server 2900 to vouch for and verify neighbors.

E. Mobile phone. A user 2916 may receive a call to a mobile phoneassociated with the user 2916 to verify their account.

F. Neighbor invitations. A neighbor who is a verified member of theprivacy server 2900 can vouch for, and may invite another neighbor tojoin the privacy server 2900. Accepting such an invitation may allow theuser 2916 to join the privacy server 2900 as a verified member,according to one embodiment.

H. Social Security Number (SSN). The privacy server 2900 can verify ahome address when the user 2916 provides the last 4 digits of a SSN(e.g., not stored by the privacy server 2900 for privacy reasons).

It will be also understood that in a preferred embodiment neighborhoodboundaries are defined by the social community module 2906 using theBezier curve algorithm 3040 of FIG. 30 may be constrained to work inneighborhoods having a threshold number of homes (e.g., 10 homes,alternatively 2900 homes in a neighborhood) and more (e.g., up tothousands of homes) as this may be needed to reach the critical mass ofactive posters that is needed to help the privacy server 2900 succeed.In one embodiment, ‘groups’ may be creatable in smaller neighborhoodshaving fewer than the threshold number of homes for communications inmicro-communities within a claimed neighborhood.

It will also be appreciated that in some embodiments, a mobile device(e.g., the device 1806, the device 1808 of FIG. 18) may be a desktopcomputer, a laptop computer, and/or a non-transitory broadcastingmodule. In addition, it will be understood that the prepopulated data(e.g., preseeded data) described herein may not be created through datalicensed from others, but rather may be user generated content oforganically created profiles in the geo-spatial social network createdby different users who have each verified their profiles.

Although the present embodiments have been described with reference tospecific example embodiments, it will be evident that variousmodifications and changes may be made to these embodiments withoutdeparting from the broader spirit and scope of the various embodiments.For example, the various devices, modules, analyzers, generators, etc.described herein may be enabled and operated using hardware circuitry(e.g., CMOS based logic circuitry), firmware, software and/or anycombination of hardware, firmware, and/or software (e.g., embodied in amachine readable medium). For example, the various electrical structureand methods may be embodied using transistors, logic gates, andelectrical circuits (e.g., application specific integrated ASICcircuitry and/or in Digital Signal; Processor DSP circuitry).

For example, the social community module 2906, the search module 2908,the claimable module 2910, the commerce module 2912, the map module2914, the building builder module 3000, the N^(th) degree module, thetagging module 3004, the verify module 3006, the groups generator module3008, the pushpin module 3010, the profile module 3012, the announcemodule 3014, the friend finder module 3022, the neighbor-neighbor helpmodule 3024, the business search module 3102, the communicate module3106, the directory assistance module 3108, the embedding module 3110,the no-match module 3112, the range selector module 3114, the user-placeclaimable module, the user-user claimable module 3202, the user—neighborclaimable module 3204, the user-business claimable module 3206, thereviews module 3208, the defamation prevention module 3210, theclaimable social network conversion module 3212, the claim module 3214,the data segment module 3216, the dispute resolution module 3218, theresident announce payment module 3300, the business displayadvertisement module 3302, the geo-position advertisement ranking module3304, the content syndication module 3306, the text advertisement module3308, the community market place module 3310, the click-in trackingmodule 3312, the satellite data module 3400, the cartoon map convertermodule 3404, the profile pointer module 3406, the parcel module 3408 andthe occupant module 3410 of FIGS. 1A-61B may be embodied through thesocial community circuit, the search circuit, the claimable circuit, thecommerce circuit, the map circuit, the building builder circuit, theN^(th) degree circuit, the tagging circuit, the verify circuit, thegroups circuit, the pushpin circuit, the profile circuit, the announcecircuit, the friends finder circuit, the neighbor-neighbor help circuit,the business search circuit, the communicate circuit, the embeddingcircuit, the no-match circuit, the range selector circuit, theuser-place claimable circuit, the user-user claimable circuit, theuser—neighbor claimable circuit, the user-business circuit, the reviewscircuit, the defamation prevention circuit, the claimable social networkconversion circuit, the claim circuit, the data segment circuit, thedispute resolution circuit, the resident announce payment circuit, thebusiness display advertisement circuit, the geo-position advertisementranking circuit, the content syndication circuit, the text advertisementcircuit, the community market place circuit, the click-in trackingcircuit, the satellite data circuit, the cartoon map converter circuit,the profile pointer circuit, the parcel circuit, the occupant circuitusing one or more of the technologies described herein.

In addition, it will be appreciated that the various operations,processes, and methods disclosed herein may be embodied in amachine-readable medium and/or a machine accessible medium compatiblewith a data processing system 4204 (e.g., a computer system), and may beperformed in any order. Accordingly, the specification and drawings areto be regarded in an illustrative rather than a restrictive sense.

What is claimed is:
 1. An autonomous neighborhood multi-coptercomprising: a set of propellers aligned in a pattern to provide theautonomous neighborhood multi-copter stability when traveling along aflight path; a storage compartment of the autonomous neighborhoodmulti-copter in which items are storable; a computer system of theautonomous neighborhood multi-copter that is communicatively coupled toa commerce server of a neighborhood communication system through awireless network to autonomously navigate the autonomous neighborhoodmulti-copter to a destination in the neighborhood specified by thecommerce server using a peer-to-peer network of client side devices inthe neighborhood that are geo-constrained to a location of a definedneighborhood; and a navigation server of the autonomous neighborhoodmulti-copter to provide a remote sensing capability to the autonomousneighborhood multi-copter such that the autonomous neighborhoodmulti-copter is autonomously navigable to the destination using thepeer-to-peer network.
 2. The autonomous neighborhood multi-copter ofclaim 1 further comprising: wherein the autonomous neighborhoodmulti-copter utilizes a sensory fusion algorithm through which at leastsome of an ultrasound s, a radar unit, a light sensor, a LIDAR unit, apropeller/wheel encoding sensor, an accelerometer sensor, a gyroscopicsensor, a compass sensor, and a stereo optical sensor operate in concertto provide a three dimensional environmental view of an environmentsurrounding the autonomous neighborhood multi-copter to the autonomousneighborhood multi-copter.
 3. The autonomous neighborhood multi-copterof claim 2 to periodically transmit a heartbeat message to the commerceserver having a set of current geo-spatial coordinates of the autonomousneighborhood multi-copter, a time stamp, a date stamp, and anoperational status of the vehicle.
 4. The autonomous neighborhoodmulti-copter of claim 3 wherein the autonomous neighborhood multi-copterautomatically generates an emergency broadcast message to a set ofneighbors in a geo-spatial vicinity of the autonomous neighborhoodmulti-copter when the autonomous neighborhood multi-copter detects afailure condition comprising at least one of an impact, a mechanicalfailure, an electrical failure, and a damage condition, wherein theemergency broadcast message includes at least one of a photo data, ageo-spatial coordinates data, a video data, an audio data, a timeoutcondition of a heartbeat message receipt at the commerce server, and atextual data associated with the failure condition.
 5. The autonomousneighborhood multi-copter of claim 4 wherein the autonomous neighborhoodmulti-copter automatically parks itself in a garage structure associatedwith an operator of the neighborhood vehicle adjacent to a passengervehicle, wherein the operator is at least one an individual, a family, abusiness, an owner, and a lessee.
 6. The autonomous neighborhoodmulti-copter of claim 5 wherein the storage compartment is temperatureregulated to maintain a temperature of an item in transit between astarting address associated with at least one of a merchant and aneighbor in a neighborhood in a geospatial vicinity of the autonomousneighborhood multi-copter, and a destination address associated with arecipient of the item in the neighborhood in the geospatial vicinity ofthe autonomous neighborhood multi-copter, wherein a neighborhoodboundary is defined through a neighborhood boundary data provider,wherein the autonomous neighborhood multi-copter is in a form of anautonomous neighborhood aerial vehicle having a detachable storagecompartment thereon, and having an ability to pilotlessly traversethrough flight path based on commands from the commerce server.
 7. Amethod of an autonomous neighborhood multi-copter comprising:associating the autonomous neighborhood multi-copter with anon-transient location; determining, through a commerce server of aneighborhood communication system, that a destination, which is in aneighborhood specified by the commerce server using a peer-to-peernetwork of client side devices in the neighborhood that aregeo-constrained to a location of a defined neighborhood and which is ina threshold radial distance from the non-transient location, is receivedby the autonomous neighborhood multi-copter through the peer-to-peerwireless network; determining an optimal route from a current locationof the autonomous neighborhood multi-copter to the destination;traveling autonomously on the optimal route to the destination;periodically determining, through a processor, the current location ofthe autonomous neighborhood multi-copter; communicating the currentlocation of the autonomous neighborhood multi-copter to the commerceserver; and automatically activating a set of light emitting diodesencompassing the autonomous neighborhood multi-copter when a lightsensor detects that an environmental brightness is below a thresholdluminosity.
 8. The method of the autonomous neighborhood multi-copter ofclaim 7 further comprising: creating an envelope around the autonomousneighborhood multi-copter, wherein the envelope includes a set ofminimum ranges, wherein the set of minimum ranges includes at least oneof a minimum distance that must be kept in at least one of a directionin front, behind, to a left, to a right, above, and below the autonomousneighborhood multi-copter; establishing at least one of a range of aspeed the autonomous vehicle may reach; establishing at least one of aminimum and a maximum distance traveled by the autonomous neighborhoodmulti-copter, wherein the minimum and the maximum distance traveled bythe autonomous neighborhood multi-copter is set for at least one of aper trip, a per day and a per delivery distance traveled; establishing amaximum magnitude of deceleration, wherein the maximum magnitude ofdeceleration is measured in feet per second squared; and establishing aminimum crosswalk proximity at which the autonomous neighborhoodmulti-copter is permitted to stop.
 9. The method of the autonomousneighborhood multi-copter of claim 8 further comprising: determining ata predetermined interval if a different route that is more efficientthan the optimal route exists based on at least one of a delivery time,a pendency of time, and a minimal travel distance, wherein thepredetermined interval for determining if the different route is moreefficient than the optimal route exists includes at least one ofconstantly determining, determining every minute, determining every onehundred yard, when the autonomous neighborhood multi-copter encounterstraffic, when the autonomous neighborhood multi-copter encounters theobject; calculating the different route; and traveling along thedifferent route as long as the different route remains a most efficientroute; determining when an alternate field of view is needed;prioritizing established constraints of at least one of the envelope,the speed, the distance traveled, a magnitude of deceleration and aminimum crosswalk proximity in respect to the need to establish thealternate field of view; determining an optimal alternate field of viewthat does not violate established constraints prioritized aboveobtaining the alternate field of view; and obtaining the optimalalternate field of view without violating constraints prioritized aboveobtaining the alternate field of view, wherein obtaining the optimalalternate field of view without violating constraints prioritized aboveobtaining the alternate field of view involves at least one of switchingsensors, moving the autonomous neighborhood multi-copter and movingsensors, and wherein the set of minimum ranges of the envelope dependson at least one of the speed of the autonomous neighborhoodmulti-copter, a set of weather conditions, an environment of theautonomous neighborhood multi-copter, the item, and a nature of theobject that is in close proximity with the autonomous neighborhoodmulti-copter, wherein the storage compartment is temperature regulatedto maintain at least one of a temperature and a humidity of an item intransit between a starting address associated with at least one of amerchant and a neighbor in a neighborhood in a geospatial vicinity ofthe autonomous neighborhood multi-copter, and a destination locationassociated with a recipient of the item in the neighborhood in thegeospatial vicinity of the autonomous neighborhood multi-copter, whereina neighborhood boundary is defined through a neighborhood boundary dataprovider, and wherein the storage compartment is equipped with asuspension device to protect the item in the storage compartment whilein transit.
 10. The method of the autonomous neighborhood multi-copterof claim 9 further comprising: automatically generating an emergencybroadcast message to a set of neighbors in a geo-spatial vicinity of theautonomous neighborhood multi-copter when the autonomous neighborhoodmulti-copter detects a failure condition comprising at least one of animpact, a mechanical failure, an electrical failure, and a damagecondition, wherein the emergency broadcast message includes at least oneof a photo data, a geo-spatial coordinates data, a video data, an audiodata, a timeout condition of a heartbeat message receipt at the commerceserver, and a textual data associated with the failure condition; andperiodically transmitting a heartbeat message to the commerce serverhaving a set of current geo-spatial coordinates of the autonomousneighborhood multi-copter, a time stamp, a date stamp, and anoperational status of the vehicle; automatically contacting emergencyresponse services when the autonomous neighborhood multi-copter detectsat least one of a crime, an accident involving third parties and anattempted tampering with the autonomous neighborhood multi-copter,wherein the contacting includes at least one of the time stamp, thegeo-spatial coordinates data, the photo data, the video data, the audiodata, and the textual data, and wherein emergency response servicesinclude at least one of a police station, a fire station and a medicalresponder; calculating a set of predicted behaviors of detected objectswithin a threshold distance from the autonomous neighborhoodmulti-copter; determining confidence levels for the predicted behaviors,wherein the confidence levels are at least one of a number and apercentage of the probability of each predicted behavior occurring; andadjusting confidence levels for the predicted behaviors based on atleast one of a change in location, a change in the speed, a change ofdirection, a change in angle and observed behavior.
 11. The method ofthe autonomous neighborhood multi-copter of claim 10 further comprising:vending the item from the storage compartment; ejecting the item from anejection module, wherein the item is ejected through an air basedpropulsion system aligned through a camera adjacent to the ejectionmodule; detecting a stop sign and automatically stopping the autonomousneighborhood multi-copter at the appropriate point when the stop sign isdetected; detecting a yield sign and automatically monitoring andyielding to a traffic flow at an intersection in the neighborhood;detecting when at least one of a pedestrian is walking and an entity isair born in a path proximate to the neighborhood vehicle; detecting whena bicyclist is biking in the path proximate to the neighborhood vehicle;and accepting a credit payment using at least one of a magnetic cardreader of the autonomous neighborhood multi-copter, a near-field creditscanner of the autonomous neighborhood multi-copter, and a biometricpayment reader of the autonomous neighborhood multi-copter.
 12. Themethod of the autonomous neighborhood multi-copter of claim 11: whereinthe commerce server is in a privacy server of the neighborhoodcommunication system that is wirelessly coupled with the autonomousneighborhood multi-copter, and wherein the privacy server is a communitynetwork comprising: verifying that each user of the community networklives at a residence associated with a claimable residential address ofthe community network formed through a social community module of theprivacy server using the processor and a memory, obtaining from eachuser of the community network, using the processor of a data processingsystem, a member data associated with each user, the member dataincluding an address, associating an address with a profile of eachuser, determining a location of each user based on the member data,storing the member data in a database, and obtaining a personal addressprivacy preference from each user, the personal address privacypreference specifying if the address should be displayed to other users.13. The method of the autonomous neighborhood multi-copter of claim 12further comprising: generating, using a mapping server associated withthe privacy server through a network, a geospatial representation of aset of points on a map defining residences associated with each user ofthe community network having the member data; and authenticating, usinga verify module of the privacy server, a particular user of athird-party application as being a verified user of the neighborhoodcommunication system having a verified residential address in theneighborhood communication system; communicating, using the verifymodule of the privacy server a social graph of the particular user basedon the personal address privacy preference of the particular user to thethird-party application; providing, using the verify module of theprivacy server, the verified residential address to the third-partyapplication based on the authentication of the particular user of thethird-party application as being the verified user of the neighborhoodcommunication system, wherein the privacy server communicatively coupledwith the mapping server through the network is configured to apply anaddress verification algorithm associated with each user of an onlinecommunity to verify that each user lives at the residence associatedwith the claimable residential address of the online community formedthrough the social community module of the privacy server using theprocessor and the memory, wherein the mapping server is configured togenerate a latitudinal data and a longitudinal data associated with eachclaimable residential address of the online community associated witheach user of the online community, wherein the privacy server isconfigured to automatically determine a set of access privileges in theonline community associated with each user of the online community byconstraining access in the online community based on a neighborhoodboundary determined using a Bezier curve algorithm of the privacyserver, wherein the privacy server is configured to transform theclaimable residential address into a claimed address upon an occurrenceof an event, wherein the privacy server is configured to instantiate theevent when the particular user is associated with the claimableresidential address based on a verification of the particular user asliving at a particular residential address associated with the claimableresidential address using the privacy server, wherein the privacy serveris configured to constrain the particular user to communicate throughthe online community only with a set of neighbors having verifiedresidential addresses using the privacy server, and wherein the privacyserver is configured to define the set of neighbors as other users ofthe online community that have each verified their addresses in theonline community using the privacy server and which have each claimedresidential addresses that are in the threshold radial distance from theclaimed address of the particular user.
 14. A neighborhood communicationsystem comprising: a commerce server; a wireless network operating in apeer-to-peer networking fashion; and a set of autonomous neighborhoodmulti-copters that are communicatively coupled to the commerce server ofthe neighborhood communication system through the wireless network toautonomously travel to destinations, which are in a neighborhoodspecified by the commerce server using the peer-to-peer wireless networkof client side devices in the neighborhood that are geo-constrained to alocation of a defined neighborhood and which are specified by thecommerce server, wherein each of the set of autonomous neighborhoodmulti-copters to periodically transmit heartbeat messages to thecommerce server having a set of current geo-spatial coordinates of eachof the autonomous neighborhood multi-copters, a time stamp, a datestamp, and an operational status of each of the autonomous neighborhoodmulti-copters, and wherein at least some of the autonomous neighborhoodmulti-copters are in a form of autonomous neighborhood aerial vehicleseach having a detachable storage compartment thereon, and having anability to autonomously traverse through flight paths based on commandsfrom the commerce server.
 15. The neighborhood communication system ofclaim 14 wherein each of the autonomous neighborhood multi-copterutilizes a sensory fusion algorithm through which at least some of anultrasound unit, a radar unit, a light sensor, a LIDAR unit, a wheelencoding sensor, an accelerometer sensor, a gyroscopic sensor, a compasssensor, and a stereo optical sensor operate in concert to provide athree dimensional environmental view to the autonomous neighborhoodmulti-copter of an environment surrounding each of the autonomousneighborhood multi-copter, and wherein a particular autonomousneighborhood multi-copter to automatically generate an emergencybroadcast message to a set of neighbors in a geo-spatial vicinity of theparticular autonomous neighborhood multi-copter when the particularautonomous neighborhood multi-copter detects a failure conditioncomprising at least one of an impact, a mechanical failure, anelectrical failure, and a damage condition, wherein the emergencybroadcast message includes at least one of a photo data, a geo-spatialcoordinates data, a video data, an audio data, a timeout condition ofthe heartbeat message receipt at the commerce server, and a textual dataassociated with the failure condition.
 16. The neighborhoodcommunication system of claim 15 wherein each of the autonomousneighborhood multi-copters automatically park themselves in a garagestructure associated with an operator of the neighborhood vehicleadjacent to a passenger vehicle, wherein the operator is at least one anindividual, a family, a business, an owner, and a lessee, wherein thestorage compartment is temperature regulated to maintain a temperatureof an item in transit between a starting address associated with atleast one of a merchant and a neighbor in a neighborhood in a geospatialvicinity of the autonomous neighborhood multi-copter, and a destinationaddress associated with a recipient of the item in the neighborhood inthe geospatial vicinity of the autonomous neighborhood multi-copter,wherein the neighborhood boundary is defined through a neighborhoodboundary data provider.
 17. The neighborhood communication system ofclaim 16 wherein the commerce server: to generate, using a mappingserver associated with the privacy server through the wireless network,a geospatial representation of a set of points on a map definingresidences associated with each user of a community network having themember data, to authenticate, using a verify module of the privacyserver, a particular user of a third-party application as being averified user of the neighborhood communication system having a verifiedresidential address in the neighborhood communication system, tocommunicate, using the verify module of the privacy server a socialgraph of the particular user based on the personal address privacypreference of the particular user to the third-party application, toprovide, using the verify module of the privacy server, the verifiedresidential address to the third-party application based on theauthentication of the particular user of the third-party application asbeing the verified user of the neighborhood communication system. 18.The neighborhood communication system of claim 17 wherein the privacyserver communicatively coupled with the mapping server through a networkto apply an address verification algorithm associated with each user ofthe online community to verify that each user lives at a residenceassociated with a claimable residential address of an online communityformed through a social community module of the privacy server using theprocessor and the memory; wherein the mapping server to generate alatitudinal data and a longitudinal data associated with each claimableresidential address of the online community associated with each user ofthe online community, wherein the privacy server to automaticallydetermine a set of access privileges in the online community associatedwith each user of the online community by constraining access in theonline community based on a neighborhood boundary determined using aBezier curve algorithm of the privacy server.
 19. The neighborhoodcommunication system of claim 18: wherein the privacy server totransform the claimable residential address into a claimed address uponan occurrence of an event, wherein the privacy server to instantiate theevent when the particular user is associated with the claimableresidential address based on a verification of the particular user asliving at a particular residential address associated with the claimableresidential address using the privacy server, wherein the privacy serverto constrain the particular user to communicate through the onlinecommunity only with the set of neighbors having verified residentialaddresses using the privacy server.
 20. The neighborhood communicationsystem of claim 19: wherein the privacy server to define the set ofneighbors as other users of the online community that have each verifiedtheir addresses in the online community using the privacy server andwhich have each claimed residential addresses that are in a thresholdradial distance from the claimed address of the particular user.